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Please note that this page does not hosts or makes available any of the listed filenames. You
cannot download any of those files from here.
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| [CourseClub.ME].url |
122B |
| [FCS Forum].url |
133B |
| [FreeCourseSite.com].url |
127B |
| 1. Become An Alumni.html |
944B |
| 1. Bonus Special Thank You Gift.html |
1.59KB |
| 1. Breaking The Flow.mp4 |
20.33MB |
| 1. Breaking The Flow.srt |
2.98KB |
| 1. Course Outline.mp4 |
77.26MB |
| 1. Course Outline.srt |
9.17KB |
| 1. Data Engineering Introduction.mp4 |
13.50MB |
| 1. Data Engineering Introduction.srt |
4.25KB |
| 1. Endorsements On LinkedIn.html |
688B |
| 1. Milestone Projects!.html |
738B |
| 1. Section Overview.mp4 |
10.19MB |
| 1. Section Overview.mp4 |
8.95MB |
| 1. Section Overview.mp4 |
12.20MB |
| 1. Section Overview.mp4 |
10.92MB |
| 1. Section Overview.mp4 |
13.35MB |
| 1. Section Overview.mp4 |
6.03MB |
| 1. Section Overview.mp4 |
10.87MB |
| 1. Section Overview.mp4 |
13.33MB |
| 1. Section Overview.mp4 |
8.60MB |
| 1. Section Overview.mp4 |
12.46MB |
| 1. Section Overview.srt |
3.11KB |
| 1. Section Overview.srt |
1.84KB |
| 1. Section Overview.srt |
2.77KB |
| 1. Section Overview.srt |
3.29KB |
| 1. Section Overview.srt |
4.65KB |
| 1. Section Overview.srt |
2.12KB |
| 1. Section Overview.srt |
3.75KB |
| 1. Section Overview.srt |
3.11KB |
| 1. Section Overview.srt |
2.69KB |
| 1. Section Overview.srt |
4.10KB |
| 1. Statistics and Mathematics.html |
710B |
| 1. The 2 Paths.mp4 |
9.75MB |
| 1. The 2 Paths.srt |
4.71KB |
| 1. What Is A Programming Language.mp4 |
104.77MB |
| 1. What Is A Programming Language.srt |
7.04KB |
| 1. What Is Machine Learning.mp4 |
28.33MB |
| 1. What Is Machine Learning.srt |
8.67KB |
| 10.1 Dataquest Jupyter Notebook for Beginners Tutorial.html |
117B |
| 10.1 Floating point numbers.html |
104B |
| 10.1 Loading TensorFlow 2.0 into a Colab Notebook (if it isn't the default).html |
129B |
| 10.1 pandas-anatomy-of-a-dataframe.png.png |
333.24KB |
| 10.1 Standard deviation and variance explained.html |
116B |
| 10.2 Jupyter Notebook documentation.html |
111B |
| 10.3 heart-disease.csv.csv |
11.06KB |
| 10. CWD Git + Github 2.mp4 |
118.35MB |
| 10. CWD Git + Github 2.srt |
18.25KB |
| 10. Filling Missing Categorical Values.mp4 |
66.91MB |
| 10. Filling Missing Categorical Values.srt |
11.20KB |
| 10. For Loops.mp4 |
34.31MB |
| 10. For Loops.srt |
7.53KB |
| 10. Jupyter Notebook Walkthrough.mp4 |
67.35MB |
| 10. Jupyter Notebook Walkthrough.srt |
15.14KB |
| 10. Manipulating Data 2.mp4 |
86.53MB |
| 10. Manipulating Data 2.srt |
13.85KB |
| 10. Modelling - Tuning.mp4 |
15.99MB |
| 10. Modelling - Tuning.srt |
4.86KB |
| 10. Numbers.mp4 |
72.71MB |
| 10. Numbers.srt |
11.13KB |
| 10. Optional Learn SQL.html |
410B |
| 10. Optional TensorFlow 2.0 Default Issue.mp4 |
28.10MB |
| 10. Optional TensorFlow 2.0 Default Issue.srt |
4.48KB |
| 10. Preparing Our Data For Machine Learning.mp4 |
72.60MB |
| 10. Preparing Our Data For Machine Learning.srt |
12.02KB |
| 10. Quick Note Regular Expressions.html |
632B |
| 10. Quick Tip Clean, Transform, Reduce.mp4 |
16.53MB |
| 10. Quick Tip Clean, Transform, Reduce.srt |
6.42KB |
| 10. Standard Deviation and Variance.mp4 |
51.16MB |
| 10. Standard Deviation and Variance.srt |
9.35KB |
| 11.1 Google Colab example GPU usage.html |
114B |
| 11.1 Introduction to Pandas Jupyter Notebook (from the videos).html |
191B |
| 11.2 Introduction to Pandas Jupyter Notebook (with annotations).html |
185B |
| 11. Choosing The Right Models.mp4 |
96.42MB |
| 11. Choosing The Right Models.srt |
12.97KB |
| 11. Contributing To Open Source.mp4 |
130.25MB |
| 11. Contributing To Open Source.srt |
17.13KB |
| 11. Fitting A Machine Learning Model.mp4 |
55.52MB |
| 11. Fitting A Machine Learning Model.srt |
10.47KB |
| 11. Getting Your Data Ready Convert Data To Numbers.mp4 |
135.02MB |
| 11. Getting Your Data Ready Convert Data To Numbers.srt |
22.71KB |
| 11. Hadoop, HDFS and MapReduce.mp4 |
10.10MB |
| 11. Hadoop, HDFS and MapReduce.srt |
4.70KB |
| 11. Iterables.mp4 |
43.20MB |
| 11. Iterables.srt |
6.85KB |
| 11. Jupyter Notebook Walkthrough 2.mp4 |
103.91MB |
| 11. Jupyter Notebook Walkthrough 2.srt |
22.48KB |
| 11. Manipulating Data 3.mp4 |
91.02MB |
| 11. Manipulating Data 3.srt |
13.71KB |
| 11. Math Functions.mp4 |
41.82MB |
| 11. Math Functions.srt |
5.43KB |
| 11. Modelling - Comparison.mp4 |
44.88MB |
| 11. Modelling - Comparison.srt |
13.09KB |
| 11. Plotting From Pandas DataFrames 2.mp4 |
98.80MB |
| 11. Plotting From Pandas DataFrames 2.srt |
13.63KB |
| 11. Reshape and Transpose.mp4 |
53.53MB |
| 11. Reshape and Transpose.srt |
9.53KB |
| 11. Using A GPU.mp4 |
80.59MB |
| 11. Using A GPU.srt |
12.11KB |
| 12.1 Google Colab Example of GPU speed up versus CPU.html |
114B |
| 12.1 Matrix Multiplication Explained.html |
119B |
| 12.1 Solution Repl.html |
92B |
| 12.2 Introduction to Google Colab example notebook.html |
116B |
| 12. Apache Spark and Apache Flink.mp4 |
5.76MB |
| 12. Apache Spark and Apache Flink.srt |
2.31KB |
| 12. Assignment Pandas Practice.html |
2.05KB |
| 12. Contributing To Open Source 2.mp4 |
113.04MB |
| 12. Contributing To Open Source 2.srt |
10.18KB |
| 12. DEVELOPER FUNDAMENTALS I.mp4 |
59.71MB |
| 12. DEVELOPER FUNDAMENTALS I.srt |
5.22KB |
| 12. Dot Product vs Element Wise.mp4 |
83.93MB |
| 12. Dot Product vs Element Wise.srt |
15.34KB |
| 12. Exercise Tricky Counter.mp4 |
16.39MB |
| 12. Exercise Tricky Counter.srt |
3.58KB |
| 12. Experimentation.mp4 |
21.33MB |
| 12. Experimentation.srt |
4.98KB |
| 12. Experimenting With Machine Learning Models.mp4 |
55.35MB |
| 12. Experimenting With Machine Learning Models.srt |
9.63KB |
| 12. Getting Your Data Ready Handling Missing Values With Pandas.mp4 |
104.84MB |
| 12. Getting Your Data Ready Handling Missing Values With Pandas.srt |
16.94KB |
| 12. Jupyter Notebook Walkthrough 3.mp4 |
71.42MB |
| 12. Jupyter Notebook Walkthrough 3.srt |
11.49KB |
| 12. Optional GPU and Google Colab.mp4 |
45.88MB |
| 12. Optional GPU and Google Colab.srt |
5.99KB |
| 12. Plotting from Pandas DataFrames 3.mp4 |
74.71MB |
| 12. Plotting from Pandas DataFrames 3.srt |
11.46KB |
| 12. Splitting Data.mp4 |
82.68MB |
| 12. Splitting Data.srt |
13.51KB |
| 13.1 Course notebooks - Github.html |
108B |
| 13.1 Exercise Repl.html |
106B |
| 13.1 heart-disease.csv.csv |
11.06KB |
| 13.2 Google Colab.html |
95B |
| 13. Coding Challenges.html |
948B |
| 13. Custom Evaluation Function.mp4 |
103.34MB |
| 13. Custom Evaluation Function.srt |
16.11KB |
| 13. Exercise Nut Butter Store Sales.mp4 |
91.33MB |
| 13. Exercise Nut Butter Store Sales.srt |
16.96KB |
| 13. Getting Your Data Ready Handling Missing Values With Scikit-learn.mp4 |
136.89MB |
| 13. Getting Your Data Ready Handling Missing Values With Scikit-learn.srt |
23.13KB |
| 13. How To Download The Course Assignments.mp4 |
66.78MB |
| 13. How To Download The Course Assignments.srt |
11.06KB |
| 13. Kafka and Stream Processing.mp4 |
19.24MB |
| 13. Kafka and Stream Processing.srt |
5.05KB |
| 13. Operator Precedence.mp4 |
14.43MB |
| 13. Operator Precedence.srt |
3.50KB |
| 13. Optional Reloading Colab Notebook.mp4 |
88.66MB |
| 13. Optional Reloading Colab Notebook.srt |
7.77KB |
| 13. Plotting from Pandas DataFrames 4.mp4 |
49.00MB |
| 13. Plotting from Pandas DataFrames 4.srt |
9.41KB |
| 13. range().mp4 |
28.32MB |
| 13. range().srt |
5.86KB |
| 13. Tools We Will Use.mp4 |
27.33MB |
| 13. Tools We Will Use.srt |
5.99KB |
| 13. TuningImproving Our Model.mp4 |
102.78MB |
| 13. TuningImproving Our Model.srt |
17.64KB |
| 14.1 Documentation on how many images Google recommends for image problems.html |
129B |
| 14.1 Exercise Repl.html |
106B |
| 14.1 Scikit-Learn machine learning map (how to choose the right machine learning model).html |
133B |
| 14. Choosing The Right Model For Your Data.mp4 |
143.26MB |
| 14. Choosing The Right Model For Your Data.srt |
21.38KB |
| 14. Comparison Operators.mp4 |
26.37MB |
| 14. Comparison Operators.srt |
5.26KB |
| 14. enumerate().mp4 |
24.80MB |
| 14. enumerate().srt |
4.56KB |
| 14. Exercise Contribute To Open Source.html |
1.43KB |
| 14. Exercise Operator Precedence.html |
683B |
| 14. Loading Our Data Labels.mp4 |
114.82MB |
| 14. Loading Our Data Labels.srt |
16.08KB |
| 14. Optional Elements of AI.html |
975B |
| 14. Plotting from Pandas DataFrames 5.mp4 |
56.96MB |
| 14. Plotting from Pandas DataFrames 5.srt |
11.63KB |
| 14. Reducing Data.mp4 |
93.47MB |
| 14. Reducing Data.srt |
14.62KB |
| 14. Tuning Hyperparameters.mp4 |
108.00MB |
| 14. Tuning Hyperparameters.srt |
15.67KB |
| 15.1 Base Numbers.html |
111B |
| 15. Choosing The Right Model For Your Data 2 (Regression).mp4 |
86.92MB |
| 15. Choosing The Right Model For Your Data 2 (Regression).srt |
11.98KB |
| 15. Optional bin() and complex.mp4 |
21.90MB |
| 15. Optional bin() and complex.srt |
4.80KB |
| 15. Plotting from Pandas DataFrames 6.mp4 |
82.04MB |
| 15. Plotting from Pandas DataFrames 6.srt |
11.08KB |
| 15. Preparing The Images.mp4 |
133.89MB |
| 15. Preparing The Images.srt |
15.12KB |
| 15. RandomizedSearchCV.mp4 |
85.83MB |
| 15. RandomizedSearchCV.srt |
12.65KB |
| 15. Sorting Arrays.mp4 |
32.83MB |
| 15. Sorting Arrays.srt |
8.80KB |
| 15. Tuning Hyperparameters 2.mp4 |
104.12MB |
| 15. Tuning Hyperparameters 2.srt |
15.10KB |
| 15. While Loops.mp4 |
28.32MB |
| 15. While Loops.srt |
7.36KB |
| 16.1 numpy-images.zip.zip |
7.27MB |
| 16.1 Python Keywords.html |
117B |
| 16.2 Introduction to NumPy Jupyter Notebook (from the videos).html |
190B |
| 16.3 Introduction to NumPy Jupyter Notebook (with annotations).html |
184B |
| 16. Improving Hyperparameters.mp4 |
79.29MB |
| 16. Improving Hyperparameters.srt |
11.03KB |
| 16. Plotting from Pandas DataFrames 7.mp4 |
119.75MB |
| 16. Plotting from Pandas DataFrames 7.srt |
14.95KB |
| 16. Quick Note Decision Trees.html |
221B |
| 16. Tuning Hyperparameters 3.mp4 |
63.01MB |
| 16. Tuning Hyperparameters 3.srt |
9.92KB |
| 16. Turn Images Into NumPy Arrays.mp4 |
85.91MB |
| 16. Turn Images Into NumPy Arrays.srt |
10.42KB |
| 16. Turning Data Labels Into Numbers.mp4 |
107.46MB |
| 16. Turning Data Labels Into Numbers.srt |
13.76KB |
| 16. Variables.mp4 |
93.56MB |
| 16. Variables.srt |
16.04KB |
| 16. While Loops 2.mp4 |
25.93MB |
| 16. While Loops 2.srt |
6.42KB |
| 17.1 Blog post by Rachel Thomas (of fast.ai) on how and why you should create a validation set.html |
108B |
| 17. Assignment NumPy Practice.html |
2.17KB |
| 17. break, continue, pass.mp4 |
22.21MB |
| 17. break, continue, pass.srt |
5.25KB |
| 17. Creating Our Own Validation Set.mp4 |
66.44MB |
| 17. Creating Our Own Validation Set.srt |
11.32KB |
| 17. Customizing Your Plots.mp4 |
92.21MB |
| 17. Customizing Your Plots.srt |
13.95KB |
| 17. Evaluating Our Model.mp4 |
71.60MB |
| 17. Evaluating Our Model.srt |
15.11KB |
| 17. Expressions vs Statements.mp4 |
10.98MB |
| 17. Expressions vs Statements.srt |
1.72KB |
| 17. Preproccessing Our Data.mp4 |
139.30MB |
| 17. Preproccessing Our Data.srt |
17.80KB |
| 17. Quick Tip How ML Algorithms Work.mp4 |
11.07MB |
| 17. Quick Tip How ML Algorithms Work.srt |
1.91KB |
| 18.1 Exercise Repl.html |
116B |
| 18.1 Solution Repl.html |
99B |
| 18.1 TensorFlow guidelines for loading all kinds of data (turning your data into Tensors).html |
98B |
| 18.2 Documentation for loading images in TensorFlow.html |
114B |
| 18.2 Exercise Repl.html |
99B |
| 18. Augmented Assignment Operator.mp4 |
15.32MB |
| 18. Augmented Assignment Operator.srt |
2.95KB |
| 18. Choosing The Right Model For Your Data 3 (Classification).mp4 |
118.84MB |
| 18. Choosing The Right Model For Your Data 3 (Classification).srt |
17.13KB |
| 18. Customizing Your Plots 2.mp4 |
123.60MB |
| 18. Customizing Your Plots 2.srt |
13.29KB |
| 18. Evaluating Our Model 2.mp4 |
41.53MB |
| 18. Evaluating Our Model 2.srt |
7.41KB |
| 18. Making Predictions.mp4 |
79.21MB |
| 18. Making Predictions.srt |
11.37KB |
| 18. Optional Extra NumPy resources.html |
1.02KB |
| 18. Our First GUI.mp4 |
49.63MB |
| 18. Our First GUI.srt |
10.37KB |
| 18. Preprocess Images.mp4 |
90.10MB |
| 18. Preprocess Images.srt |
12.93KB |
| 19.1 End-to-end Bluebook Bulldozer Regression Notebook (with annotations).html |
208B |
| 19.1 Introduction to Matplotlib Notebook (from the videos).html |
195B |
| 19.2 End-to-end Bluebook Bulldozer Regression Notebook (same as in videos).html |
214B |
| 19. DEVELOPER FUNDAMENTALS IV.mp4 |
50.22MB |
| 19. DEVELOPER FUNDAMENTALS IV.srt |
7.82KB |
| 19. Evaluating Our Model 3.mp4 |
64.84MB |
| 19. Evaluating Our Model 3.srt |
11.55KB |
| 19. Feature Importance.mp4 |
142.30MB |
| 19. Feature Importance.srt |
17.26KB |
| 19. Fitting A Model To The Data.mp4 |
56.56MB |
| 19. Fitting A Model To The Data.srt |
9.33KB |
| 19. Preprocess Images 2.mp4 |
105.07MB |
| 19. Preprocess Images 2.srt |
12.89KB |
| 19. Saving And Sharing Your Plots.mp4 |
49.52MB |
| 19. Saving And Sharing Your Plots.srt |
5.83KB |
| 19. Strings.mp4 |
30.98MB |
| 19. Strings.srt |
6.29KB |
| 2.1 End-to-end Heart Disease Classification Notebook (same as in videos).html |
207B |
| 2.1 Introduction to Scikit-Learn Jupyter Notebook (from the upcoming videos).html |
197B |
| 2.1 Kaggle.html |
92B |
| 2.1 Kaggle Bluebook for Bulldozers Competition.html |
118B |
| 2.1 Matplotlib Documentation.html |
103B |
| 2.1 NumPy Documentation.html |
83B |
| 2.2 End-to-end Bluebook Bulldozer Regression Notebook (with annotations).html |
208B |
| 2.2 Introduction to Matplotlib Jupyter Notebook (from the upcoming videos).html |
195B |
| 2.2 Introduction to NumPy Jupyter Notebook (from the upcoming videos).html |
190B |
| 2.2 Introduction to Scikit-Learn Jupyter Notebook (with annotations).html |
191B |
| 2.2 Structured Data Projects on GitHub.html |
155B |
| 2.3 End-to-end Heart Disease Classification Notebook (with annotations).html |
201B |
| 2.3 Introduction to NumPy Jupyter Notebook (with annotations).html |
184B |
| 2.3 Scikit-Learn Documentation.html |
108B |
| 2.3 Structured Data Projects on GitHub.html |
155B |
| 2.4 End-to-end Bluebook Bulldozer Regression Notebook (same as in videos).html |
214B |
| 2. AIMachine LearningData Science.mp4 |
19.67MB |
| 2. AIMachine LearningData Science.srt |
6.36KB |
| 2. Conditional Logic.mp4 |
74.58MB |
| 2. Conditional Logic.srt |
15.66KB |
| 2. Deep Learning and Unstructured Data.mp4 |
102.04MB |
| 2. Deep Learning and Unstructured Data.srt |
20.20KB |
| 2. Downloading Workbooks and Assignments.html |
774B |
| 2. Introducing Our Framework.mp4 |
11.38MB |
| 2. Introducing Our Framework.srt |
3.70KB |
| 2. Introducing Our Tools.mp4 |
19.29MB |
| 2. Introducing Our Tools.srt |
4.34KB |
| 2. Join Our Online Classroom!.html |
2.27KB |
| 2. Matplotlib Introduction.mp4 |
31.51MB |
| 2. Matplotlib Introduction.srt |
8.03KB |
| 2. NumPy Introduction.mp4 |
26.84MB |
| 2. NumPy Introduction.srt |
7.50KB |
| 2. Project Overview.mp4 |
34.44MB |
| 2. Project Overview.mp4 |
32.94MB |
| 2. Project Overview.srt |
10.02KB |
| 2. Project Overview.srt |
6.66KB |
| 2. Python Developer Monthly.html |
476B |
| 2. Python Interpreter.mp4 |
93.47MB |
| 2. Python Interpreter.srt |
8.30KB |
| 2. Quick Note Upcoming Video.html |
587B |
| 2. Scikit-learn Introduction.mp4 |
40.63MB |
| 2. Scikit-learn Introduction.srt |
10.60KB |
| 2. Thank You.mp4 |
11.11MB |
| 2. Thank You.srt |
3.64KB |
| 2. Videos uploaded by FEB 14th.html |
203B |
| 2. What Is Data.mp4 |
42.22MB |
| 2. What Is Data.srt |
7.62KB |
| 20.1 Solution Repl.html |
102B |
| 20. Assignment Matplotlib Practice.html |
2.05KB |
| 20. Exercise Find Duplicates.mp4 |
20.25MB |
| 20. Exercise Find Duplicates.srt |
4.39KB |
| 20. Finding The Most Important Features.mp4 |
127.49MB |
| 20. Finding The Most Important Features.srt |
22.33KB |
| 20. Making Predictions With Our Model.mp4 |
66.50MB |
| 20. Making Predictions With Our Model.srt |
12.08KB |
| 20. String Concatenation.mp4 |
7.34MB |
| 20. String Concatenation.srt |
1.42KB |
| 20. Turning Data Into Batches.mp4 |
87.77MB |
| 20. Turning Data Into Batches.srt |
11.61KB |
| 21.1 End-to-end Heart Disease Classification Notebook (with annotations).html |
201B |
| 21.1 Yann LeCun's (OG of deep learning) Tweet on Batch Sizes.html |
118B |
| 21.2 End-to-end Heart Disease Classification Notebook (same as in videos).html |
207B |
| 21. Functions.mp4 |
48.60MB |
| 21. Functions.srt |
9.20KB |
| 21. predict() vs predict_proba().mp4 |
54.33MB |
| 21. predict() vs predict_proba().srt |
11.56KB |
| 21. Reviewing The Project.mp4 |
86.14MB |
| 21. Reviewing The Project.srt |
13.81KB |
| 21. Turning Data Into Batches 2.mp4 |
149.38MB |
| 21. Turning Data Into Batches 2.srt |
20.15KB |
| 21. Type Conversion.mp4 |
18.99MB |
| 21. Type Conversion.srt |
3.09KB |
| 22. Escape Sequences.mp4 |
23.15MB |
| 22. Escape Sequences.srt |
5.01KB |
| 22. Making Predictions With Our Model (Regression).mp4 |
44.91MB |
| 22. Making Predictions With Our Model (Regression).srt |
9.13KB |
| 22. Parameters and Arguments.mp4 |
23.14MB |
| 22. Parameters and Arguments.srt |
4.88KB |
| 22. Visualizing Our Data.mp4 |
121.99MB |
| 22. Visualizing Our Data.srt |
15.66KB |
| 23.1 Exercise Repl.html |
104B |
| 23.1 TensorFlow Hub (resource for pre-trained deep learning models and more).html |
79B |
| 23. Default Parameters and Keyword Arguments.mp4 |
38.14MB |
| 23. Default Parameters and Keyword Arguments.srt |
5.98KB |
| 23. Evaluating A Machine Learning Model (Score).mp4 |
87.13MB |
| 23. Evaluating A Machine Learning Model (Score).srt |
12.86KB |
| 23. Formatted Strings.mp4 |
49.25MB |
| 23. Formatted Strings.srt |
8.84KB |
| 23. Preparing Our Inputs and Outputs.mp4 |
50.07MB |
| 23. Preparing Our Inputs and Outputs.srt |
7.78KB |
| 24.1 Exercise Repl.html |
101B |
| 24. Evaluating A Machine Learning Model 2 (Cross Validation).mp4 |
95.97MB |
| 24. Evaluating A Machine Learning Model 2 (Cross Validation).srt |
17.25KB |
| 24. Optional How machines learn and what's going on behind the scenes.html |
2.72KB |
| 24. return.mp4 |
63.04MB |
| 24. return.srt |
14.97KB |
| 24. String Indexes.mp4 |
49.15MB |
| 24. String Indexes.srt |
9.21KB |
| 25.1 Andrei Karpathy's talk on AI at Tesla.html |
95B |
| 25.2 PyTorch Hub (PyTorch version of TensorFlow Hub).html |
85B |
| 25.3 Papers with Code (a great resource for some of the best machine learning papers with code examples).html |
88B |
| 25.4 TensorFlow Hub (resource for pre-trained deep learning models and more).html |
79B |
| 25.5 MobileNetV2 (the model we're using) on TensorFlow Hub.html |
132B |
| 25. Building A Deep Learning Model.mp4 |
121.85MB |
| 25. Building A Deep Learning Model.srt |
15.92KB |
| 25. Evaluating A Classification Model 1 (Accuracy).mp4 |
31.41MB |
| 25. Evaluating A Classification Model 1 (Accuracy).srt |
5.87KB |
| 25. Exercise Tesla.html |
402B |
| 25. Immutability.mp4 |
20.80MB |
| 25. Immutability.srt |
3.50KB |
| 26.1 Keras in TensorFlow Overview Documentation.html |
108B |
| 26.1 String Methods.html |
115B |
| 26.2 Built in Functions.html |
109B |
| 26. Building A Deep Learning Model 2.mp4 |
105.90MB |
| 26. Building A Deep Learning Model 2.srt |
12.54KB |
| 26. Built-In Functions + Methods.mp4 |
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| 26. Built-In Functions + Methods.srt |
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| 26. Evaluating A Classification Model 2 (ROC Curve).mp4 |
66.03MB |
| 26. Evaluating A Classification Model 2 (ROC Curve).srt |
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| 26. Methods vs Functions.mp4 |
30.69MB |
| 26. Methods vs Functions.srt |
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| 27.1 The Softmax Function (activation function we use in our model).html |
107B |
| 27.2 Step by step breakdown of a convolutional neural network (what MobileNetV2 is made of).html |
172B |
| 27.3 MobileNetV2 (the model we're using) architecture explanation by Sik-Ho Tsang.html |
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| 27. Booleans.mp4 |
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| 27. Booleans.srt |
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| 27. Building A Deep Learning Model 3.mp4 |
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| 27. Building A Deep Learning Model 3.srt |
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| 27. Docstrings.mp4 |
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| 27. Docstrings.srt |
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| 27. Evaluating A Classification Model 3 (ROC Curve).mp4 |
50.61MB |
| 27. Evaluating A Classification Model 3 (ROC Curve).srt |
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| 28.1 [Article] How to choose loss & activation functions when building a deep learning model.html |
169B |
| 28. Building A Deep Learning Model 4.mp4 |
86.30MB |
| 28. Building A Deep Learning Model 4.srt |
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| 28. Clean Code.mp4 |
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| 28. Clean Code.srt |
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| 28. Evaluating A Classification Model 4 (Confusion Matrix).mp4 |
77.72MB |
| 28. Evaluating A Classification Model 4 (Confusion Matrix).srt |
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| 28. Exercise Type Conversion.mp4 |
50.34MB |
| 28. Exercise Type Conversion.srt |
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| 29.1 Python Comments Best Practices.html |
106B |
| 29. args and kwargs.mp4 |
43.02MB |
| 29. args and kwargs.srt |
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| 29. DEVELOPER FUNDAMENTALS II.mp4 |
29.25MB |
| 29. DEVELOPER FUNDAMENTALS II.srt |
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| 29. Evaluating A Classification Model 5 (Confusion Matrix).mp4 |
63.59MB |
| 29. Evaluating A Classification Model 5 (Confusion Matrix).srt |
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| 29. Summarizing Our Model.mp4 |
45.44MB |
| 29. Summarizing Our Model.srt |
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| 3.1 A 6 Step Field Guide for Machine Learning Modelling (blog post).html |
147B |
| 3.1 Getting your computer ready for machine learning How, what and why you should use Anaconda, Miniconda and Conda (blog post).html |
167B |
| 3.1 Pandas Documentation.html |
106B |
| 3.1 Teachable Machine.html |
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132B |
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139B |
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| 3.3 Introduction to Pandas Jupyter Notebook (from the upcoming videos).html |
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23.46MB |
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| 3. Exercise Machine Learning Playground.mp4 |
42.59MB |
| 3. Exercise Machine Learning Playground.srt |
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63.90MB |
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| 3. Pandas Introduction.mp4 |
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100.76MB |
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101.27MB |
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| 3. Quick Note Correction In Next Video.html |
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| 3. Quick Note Upcoming Video.html |
390B |
| 3. Setting Up With Google.html |
568B |
| 3. What If I Don't Have Enough Experience.mp4 |
160.94MB |
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| 3. What Is A Data Engineer.mp4 |
15.16MB |
| 3. What Is A Data Engineer.srt |
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| 3. What is Conda.mp4 |
12.48MB |
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| 30.1 Solution Repl.html |
108B |
| 30.1 TensorBoard Callback Documentation.html |
134B |
| 30. Evaluating A Classification Model 6 (Classification Report).mp4 |
87.24MB |
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| 30. Evaluating Our Model.mp4 |
79.29MB |
| 30. Evaluating Our Model.srt |
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| 30. Exercise Functions.mp4 |
21.85MB |
| 30. Exercise Functions.srt |
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| 30. Exercise Password Checker.mp4 |
51.09MB |
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| 31.1 Early Stopping Callback (a way to stop your model from training when it stops improving) Documentation.html |
136B |
| 31. Evaluating A Regression Model 1 (R2 Score).mp4 |
70.39MB |
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| 31. Lists.mp4 |
21.96MB |
| 31. Lists.srt |
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| 31. Preventing Overfitting.mp4 |
36.51MB |
| 31. Preventing Overfitting.srt |
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| 31. Scope.mp4 |
20.15MB |
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| 32. Evaluating A Regression Model 2 (MAE).mp4 |
28.52MB |
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| 32. List Slicing.mp4 |
49.86MB |
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| 32. Scope Rules.mp4 |
37.68MB |
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| 32. Training Your Deep Neural Network.mp4 |
166.60MB |
| 32. Training Your Deep Neural Network.srt |
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| 33.1 Exercise Repl.html |
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| 33. Evaluating A Regression Model 3 (MSE).mp4 |
54.90MB |
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| 33. Evaluating Performance With TensorBoard.mp4 |
74.18MB |
| 33. Evaluating Performance With TensorBoard.srt |
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| 33. global Keyword.mp4 |
36.50MB |
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| 33. Matrix.mp4 |
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| 34.1 List Methods.html |
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| 34.1 Solution Repl.html |
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| 34. List Methods.mp4 |
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| 34. Make And Transform Predictons.mp4 |
154.98MB |
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| 34. nonlocal Keyword.mp4 |
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| 35.1 Exercise Repl.html |
94B |
| 35.1 TensorFlow documentation for the unbatch() function.html |
127B |
| 35.2 Python Keywords.html |
117B |
| 35. Evaluating A Model With Cross Validation and Scoring Parameter.mp4 |
91.49MB |
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| 35. List Methods 2.mp4 |
27.40MB |
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| 35. Transform Predictions To Text.mp4 |
129.87MB |
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| 35. Why Do We Need Scope.mp4 |
19.18MB |
| 35. Why Do We Need Scope.srt |
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| 36. Evaluating A Model With Scikit-learn Functions.mp4 |
94.82MB |
| 36. Evaluating A Model With Scikit-learn Functions.srt |
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| 36. List Methods 3.mp4 |
27.66MB |
| 36. List Methods 3.srt |
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| 36. Pure Functions.mp4 |
67.36MB |
| 36. Pure Functions.srt |
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| 36. Visualizing Model Predictions.mp4 |
119.31MB |
| 36. Visualizing Model Predictions.srt |
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| 37.1 Exercise Repl.html |
94B |
| 37. Common List Patterns.mp4 |
40.46MB |
| 37. Common List Patterns.srt |
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| 37. Improving A Machine Learning Model.mp4 |
90.93MB |
| 37. Improving A Machine Learning Model.srt |
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| 37. map().mp4 |
38.38MB |
| 37. map().srt |
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| 37. Visualizing And Evaluate Model Predictions 2.mp4 |
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| 38. filter().mp4 |
23.55MB |
| 38. filter().srt |
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| 38. List Unpacking.mp4 |
13.86MB |
| 38. List Unpacking.srt |
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| 38. Tuning Hyperparameters.mp4 |
175.53MB |
| 38. Tuning Hyperparameters.srt |
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| 38. Visualizing And Evaluate Model Predictions 3.mp4 |
113.21MB |
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| 39. None.mp4 |
7.93MB |
| 39. None.srt |
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| 39. Saving And Loading A Trained Model.mp4 |
126.98MB |
| 39. Saving And Loading A Trained Model.srt |
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| 39. Tuning Hyperparameters 2.mp4 |
116.77MB |
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| 39. zip().mp4 |
21.27MB |
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| 4.1 Kaggle Dog Breed Identification Competition (the basis of our upcoming project).html |
119B |
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| 4.1 Truthy vs Falsey Stackoverflow.html |
170B |
| 4.2 Google Colab (our workspace for the upcoming project).html |
95B |
| 4.2 matplotlib-anatomy-of-a-plot-with-code.png.png |
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| 4.3 Introduction to Google Colab example notebook.html |
116B |
| 4.4 Google Colab IO example (how to get data in and out of your Colab notebook).html |
113B |
| 4.5 End-to-end Dog Vision Notebook (the project we'll be working through).html |
182B |
| 4. Anatomy Of A Matplotlib Figure.mp4 |
82.15MB |
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| 4. Conda Environments.mp4 |
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| 4. How Did We Get Here.mp4 |
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| 4. Learning Guideline.html |
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| 4. NumPy DataTypes and Attributes.mp4 |
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| 4. Our First Python Program.mp4 |
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| 4. Refresher What Is Machine Learning.mp4 |
88.27MB |
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| 4. Series, Data Frames and CSVs.mp4 |
95.37MB |
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| 4. Setting Up Google Colab.mp4 |
74.24MB |
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105.50MB |
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85.69MB |
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| 4. Truthy vs Falsey.mp4 |
42.82MB |
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| 4. Types of Machine Learning Problems.mp4 |
60.50MB |
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| 4. What Is A Data Engineer 2.mp4 |
24.23MB |
| 4. What Is A Data Engineer 2.srt |
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| 4. Your First Day.mp4 |
27.92MB |
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| 40. Dictionaries.mp4 |
32.70MB |
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| 40. reduce().mp4 |
52.27MB |
| 40. reduce().srt |
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| 40. Training Model On Full Dataset.mp4 |
139.82MB |
| 40. Training Model On Full Dataset.srt |
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| 40. Tuning Hyperparameters 3.mp4 |
121.76MB |
| 40. Tuning Hyperparameters 3.srt |
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| 41.1 Dog Vision Prediction Probabilities Array.html |
170B |
| 41. DEVELOPER FUNDAMENTALS III.mp4 |
26.63MB |
| 41. DEVELOPER FUNDAMENTALS III.srt |
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| 41. List Comprehensions.mp4 |
53.34MB |
| 41. List Comprehensions.srt |
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| 41. Making Predictions On Test Images.mp4 |
140.83MB |
| 41. Quick Tip Correlation Analysis.mp4 |
16.92MB |
| 41. Quick Tip Correlation Analysis.srt |
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| 42.1 Dog Vision Predictions with MobileNetV2 Ready for Kaggle Submission.html |
180B |
| 42. Dictionary Keys.mp4 |
20.37MB |
| 42. Dictionary Keys.srt |
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| 42. Saving And Loading A Model.mp4 |
52.60MB |
| 42. Saving And Loading A Model.srt |
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| 42. Set Comprehensions.mp4 |
35.37MB |
| 42. Set Comprehensions.srt |
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| 42. Submitting Model to Kaggle.mp4 |
121.34MB |
| 43.1 Dictionary Methods.html |
119B |
| 43.1 End-to-end Dog Vision Notebook (with annotations).html |
185B |
| 43.1 Solution Repl.html |
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| 43.2 End-to-end Dog Vision Notebook (from the videos).html |
191B |
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| 43. Exercise Comprehensions.mp4 |
21.96MB |
| 43. Exercise Comprehensions.srt |
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| 43. Making Predictions On Our Images.mp4 |
119.24MB |
| 43. Saving And Loading A Model 2.mp4 |
56.77MB |
| 43. Saving And Loading A Model 2.srt |
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| 44.1 Exercise Repl.html |
97B |
| 44. Dictionary Methods 2.mp4 |
42.39MB |
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| 44. Finishing Dog Vision Where to next.html |
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| 44. Putting It All Together.mp4 |
158.35MB |
| 44. Putting It All Together.srt |
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| 44. Python Exam Testing Your Understanding.html |
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| 45.1 Introduction to Scikit-Learn Jupyter Notebook (from the videos).html |
197B |
| 45.2 Introduction to Scikit-Learn Jupyter Notebook (with annotations).html |
191B |
| 45. Modules in Python.mp4 |
82.18MB |
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| 45. Putting It All Together 2.mp4 |
116.85MB |
| 45. Putting It All Together 2.srt |
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| 45. Tuples.mp4 |
25.65MB |
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114B |
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448B |
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17.00MB |
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53.06MB |
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| 47. Sets.mp4 |
36.98MB |
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91B |
| 48.2 Sets Methods.html |
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| 48. Packages in Python.mp4 |
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| 48. Sets 2.mp4 |
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| 49. Different Ways To Import.mp4 |
47.96MB |
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| 5.1 Google Colab FAQ (things you should know about Google Colab).html |
110B |
| 5.1 Machine Learning Playground.html |
88B |
| 5.1 Miniconda download documentation.html |
107B |
| 5.1 The Story of Python.html |
104B |
| 5.2 Google Colab (our workspace for the upcoming project).html |
95B |
| 5.2 Python 2 vs Python 3.html |
161B |
| 5. Creating NumPy Arrays.mp4 |
66.77MB |
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19.43MB |
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| 5. Exploring Our Data.mp4 |
137.81MB |
| 5. Exploring Our Data.srt |
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| 5. Getting Our Tools Ready.mp4 |
79.36MB |
| 5. Getting Our Tools Ready.srt |
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| 5. Google Colab Workspace.mp4 |
39.63MB |
| 5. Google Colab Workspace.srt |
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| 5. Mac Environment Setup.mp4 |
144.39MB |
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| 5. Python 2 vs Python 3.mp4 |
82.14MB |
| 5. Python 2 vs Python 3.srt |
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565B |
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| 5. Scatter Plot And Bar Plot.mp4 |
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| 5. Ternary Operator.mp4 |
19.71MB |
| 5. Ternary Operator.srt |
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| 5. Types of Data.mp4 |
29.32MB |
| 5. Types of Data.srt |
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| 5. What Is A Data Engineer 3.mp4 |
24.29MB |
| 5. What Is A Data Engineer 3.srt |
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| 50. Next Steps.html |
959B |
| 6.1 heart-disease.csv.csv |
11.06KB |
| 6.1 Kaggle Dog Breed Identification Competition Data.html |
115B |
| 6.1 Scikit-Learn Reference Notebook.html |
194B |
| 6.2 Google Colab IO example (how to get data in and out of your Colab notebook).html |
113B |
| 6. Describing Data with Pandas.mp4 |
75.56MB |
| 6. Describing Data with Pandas.srt |
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| 6. Exercise How Does Python Work.mp4 |
25.96MB |
| 6. Exercise How Does Python Work.srt |
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| 6. Exploring Our Data.mp4 |
66.88MB |
| 6. Exploring Our Data.srt |
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| 6. Exploring Our Data 2.mp4 |
52.04MB |
| 6. Exploring Our Data 2.srt |
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| 6. Histograms And Subplots.mp4 |
69.75MB |
| 6. Histograms And Subplots.srt |
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| 6. JTS Learn to Learn.mp4 |
11.14MB |
| 6. JTS Learn to Learn.srt |
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125.46MB |
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| 6. NumPy Random Seed.mp4 |
51.92MB |
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| 6. Scikit-learn Cheatsheet.mp4 |
75.13MB |
| 6. Scikit-learn Cheatsheet.srt |
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| 6. Short Circuiting.mp4 |
19.40MB |
| 6. Short Circuiting.srt |
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| 6. Types of Evaluation.mp4 |
17.75MB |
| 6. Types of Evaluation.srt |
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| 6. Types of Machine Learning.mp4 |
22.75MB |
| 6. Types of Machine Learning.srt |
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| 6. Uploading Project Data.mp4 |
51.98MB |
| 6. Uploading Project Data.srt |
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| 6. What Is A Data Engineer 4.mp4 |
14.93MB |
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| 7.1 car-sales.csv.csv |
369B |
| 7.1 Example Scikit-Learn Workflow Notebook.html |
192B |
| 7.1 Miniconda download documentation.html |
107B |
| 7.1 OLTP vs OLAP.html |
126B |
| 7.2 A Primer on ACID Transactions.html |
117B |
| 7. Are You Getting It Yet.html |
160B |
| 7. Feature Engineering.mp4 |
159.14MB |
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| 7. Features In Data.mp4 |
36.78MB |
| 7. Features In Data.srt |
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| 7. Finding Patterns.mp4 |
63.34MB |
| 7. Finding Patterns.srt |
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| 7. JTS Start With Why.mp4 |
15.43MB |
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| 7. Learning Python.mp4 |
38.52MB |
| 7. Learning Python.srt |
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| 7. Logical Operators.mp4 |
28.33MB |
| 7. Logical Operators.srt |
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| 7. Selecting and Viewing Data with Pandas.mp4 |
72.35MB |
| 7. Selecting and Viewing Data with Pandas.srt |
14.59KB |
| 7. Setting Up Our Data.mp4 |
42.26MB |
| 7. Setting Up Our Data.srt |
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| 7. Subplots Option 2.mp4 |
38.09MB |
| 7. Subplots Option 2.srt |
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| 7. Types Of Databases.mp4 |
32.55MB |
| 7. Types Of Databases.srt |
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| 7. Typical scikit-learn Workflow.mp4 |
190.18MB |
| 7. Typical scikit-learn Workflow.srt |
31.71KB |
| 7. Viewing Arrays and Matrices.mp4 |
70.64MB |
| 7. Viewing Arrays and Matrices.srt |
12.89KB |
| 7. Windows Environment Setup.mp4 |
47.92MB |
| 7. Windows Environment Setup.srt |
7.62KB |
| 8.1 Standard deviation and variance explained.html |
116B |
| 8. Exercise Logical Operators.mp4 |
46.62MB |
| 8. Exercise Logical Operators.srt |
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| 8. Finding Patterns 2.mp4 |
99.92MB |
| 8. Finding Patterns 2.srt |
22.32KB |
| 8. Manipulating Arrays.mp4 |
80.65MB |
| 8. Manipulating Arrays.srt |
16.17KB |
| 8. Modelling - Splitting Data.mp4 |
27.51MB |
| 8. Modelling - Splitting Data.srt |
7.71KB |
| 8. Optional Debugging Warnings In Jupyter.mp4 |
176.13MB |
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25.51KB |
| 8. Python Data Types.mp4 |
28.85MB |
| 8. Python Data Types.srt |
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| 8. Quick Note Upcoming Video.html |
481B |
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352B |
| 8. Quick Tip Data Visualizations.mp4 |
12.25MB |
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| 8. Selecting and Viewing Data with Pandas Part 2.mp4 |
106.50MB |
| 8. Selecting and Viewing Data with Pandas Part 2.srt |
17.92KB |
| 8. Setting Up Our Data 2.mp4 |
20.87MB |
| 8. Setting Up Our Data 2.srt |
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| 8. Turning Data Into Numbers.mp4 |
146.17MB |
| 8. Turning Data Into Numbers.srt |
22.32KB |
| 8. What Is Machine Learning Round 2.mp4 |
25.51MB |
| 8. What Is Machine Learning Round 2.srt |
6.07KB |
| 8. Windows Environment Setup 2.mp4 |
227.60MB |
| 8. Windows Environment Setup 2.srt |
31.61KB |
| 9.1 car-sales-extended-missing-data.csv.csv |
30.20KB |
| 9.1 Pandas Categorical Datatype Documentation.html |
143B |
| 9.1 Standard deviation and variance explained.html |
116B |
| 9.2 Jake VanderPlas's Data Manipulation with Pandas.html |
146B |
| 9. CWD Git + Github.mp4 |
176.12MB |
| 9. CWD Git + Github.srt |
21.17KB |
| 9. Filling Missing Numerical Values.mp4 |
106.34MB |
| 9. Filling Missing Numerical Values.srt |
16.94KB |
| 9. Finding Patterns 3.mp4 |
137.86MB |
| 9. Finding Patterns 3.srt |
18.88KB |
| 9. Getting Your Data Ready Splitting Your Data.mp4 |
63.66MB |
| 9. Getting Your Data Ready Splitting Your Data.srt |
12.08KB |
| 9. How To Succeed.html |
280B |
| 9. Importing TensorFlow 2.mp4 |
116.76MB |
| 9. Importing TensorFlow 2.srt |
16.79KB |
| 9. is vs ==.mp4 |
33.57MB |
| 9. is vs ==.srt |
8.12KB |
| 9. Linux Environment Setup.html |
1.03KB |
| 9. Manipulating Arrays 2.mp4 |
67.90MB |
| 9. Manipulating Arrays 2.srt |
11.49KB |
| 9. Manipulating Data.mp4 |
104.99MB |
| 9. Manipulating Data.srt |
18.07KB |
| 9. Modelling - Picking the Model.mp4 |
23.24MB |
| 9. Modelling - Picking the Model.srt |
6.21KB |
| 9. Optional OLTP Databases.mp4 |
79.68MB |
| 9. Optional OLTP Databases.srt |
12.11KB |
| 9. Plotting From Pandas DataFrames.mp4 |
60.35MB |
| 9. Plotting From Pandas DataFrames.srt |
9.02KB |
| 9. Section Review.mp4 |
5.57MB |
| 9. Section Review.srt |
2.34KB |