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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. Applications of Machine Learning.mp4 |
7.99MB |
| 1. Applications of Machine Learning.vtt |
4.64KB |
| 1. Apriori Intuition.mp4 |
35.02MB |
| 1. Apriori Intuition.vtt |
22.59KB |
| 1. Bayes Theorem.mp4 |
43.90MB |
| 1. Bayes Theorem.vtt |
30.66KB |
| 1. Decision Tree Classification Intuition.mp4 |
18.79MB |
| 1. Decision Tree Classification Intuition.vtt |
18.80MB |
| 1. Decision Tree Regression Intuition.mp4 |
22.69MB |
| 1. Decision Tree Regression Intuition.vtt |
15.25KB |
| 1. Eclat Intuition.mp4 |
10.65MB |
| 1. Eclat Intuition.vtt |
7.12KB |
| 1. False Positives & False Negatives.mp4 |
13.65MB |
| 1. False Positives & False Negatives.vtt |
10.19KB |
| 1. Hierarchical Clustering Intuition.mp4 |
16.53MB |
| 1. Hierarchical Clustering Intuition.vtt |
16.53MB |
| 1. How to get the dataset.mp4 |
11.71MB |
| 1. How to get the dataset.mp4 |
11.72MB |
| 1. How to get the dataset.mp4 |
11.71MB |
| 1. How to get the dataset.mp4 |
11.71MB |
| 1. How to get the dataset.mp4 |
11.71MB |
| 1. How to get the dataset.mp4 |
11.71MB |
| 1. How to get the dataset.vtt |
4.23KB |
| 1. How to get the dataset.vtt |
11.72MB |
| 1. How to get the dataset.vtt |
4.23KB |
| 1. How to get the dataset.vtt |
4.23KB |
| 1. How to get the dataset.vtt |
4.23KB |
| 1. How to get the dataset.vtt |
4.23KB |
| 1. Kernel SVM Intuition.mp4 |
5.79MB |
| 1. Kernel SVM Intuition.vtt |
3.92KB |
| 1. K-Means Clustering Intuition.mp4 |
26.86MB |
| 1. K-Means Clustering Intuition.vtt |
20.91KB |
| 1. K-Nearest Neighbor Intuition.mp4 |
9.28MB |
| 1. K-Nearest Neighbor Intuition.vtt |
7.23KB |
| 1. Linear Discriminant Analysis (LDA) Intuition.mp4 |
26.98MB |
| 1. Linear Discriminant Analysis (LDA) Intuition.vtt |
4.53KB |
| 1. Logistic Regression Intuition.mp4 |
29.17MB |
| 1. Logistic Regression Intuition.vtt |
20.91KB |
| 1. Plan of attack.mp4 |
4.74MB |
| 1. Plan of attack.mp4 |
5.90MB |
| 1. Plan of attack.vtt |
3.54KB |
| 1. Plan of attack.vtt |
4.63KB |
| 1. Polynomial Regression Intuition.mp4 |
9.44MB |
| 1. Polynomial Regression Intuition.vtt |
7.07KB |
| 1. Principal Component Analysis (PCA) Intuition.mp4 |
32.11MB |
| 1. Principal Component Analysis (PCA) Intuition.vtt |
4.45KB |
| 1. Random Forest Classification Intuition.mp4 |
19.43MB |
| 1. Random Forest Classification Intuition.vtt |
6.41KB |
| 1. Random Forest Regression Intuition.mp4 |
13.82MB |
| 1. Random Forest Regression Intuition.vtt |
9.29KB |
| 1. R-Squared Intuition.mp4 |
8.85MB |
| 1. R-Squared Intuition.vtt |
6.46KB |
| 1. SVM Intuition.mp4 |
18.01MB |
| 1. SVM Intuition.vtt |
14.19KB |
| 1. The Multi-Armed Bandit Problem.mp4 |
30.19MB |
| 1. The Multi-Armed Bandit Problem.vtt |
19.44KB |
| 1. Thompson Sampling Intuition.mp4 |
37.27MB |
| 1. Thompson Sampling Intuition.vtt |
24.09KB |
| 1. Welcome to Part 10 - Model Selection & Boosting.html |
899B |
| 1. Welcome to Part 1 - Data Preprocessing.mp4 |
2.99MB |
| 1. Welcome to Part 1 - Data Preprocessing.vtt |
2.29KB |
| 1. Welcome to Part 2 - Regression.html |
875B |
| 1. Welcome to Part 3 - Classification.html |
831B |
| 1. Welcome to Part 4 - Clustering.html |
734B |
| 1. Welcome to Part 5 - Association Rule Learning.html |
425B |
| 1. Welcome to Part 6 - Reinforcement Learning.html |
804B |
| 1. Welcome to Part 7 - Natural Language Processing.html |
1.69KB |
| 1. Welcome to Part 8 - Deep Learning.html |
870B |
| 1. Welcome to Part 9 - Dimensionality Reduction.html |
1.26KB |
| 1. YOUR SPECIAL BONUS.html |
4.54KB |
| 10. Business Problem Description.mp4 |
16.38MB |
| 10. Business Problem Description.vtt |
6.47KB |
| 10. Feature Scaling.mp4 |
34.62MB |
| 10. Feature Scaling.vtt |
20.79KB |
| 10. HC in R - Step 1.mp4 |
7.38MB |
| 10. HC in R - Step 1.vtt |
5.67KB |
| 10. How to get the dataset.mp4 |
11.71MB |
| 10. How to get the dataset.vtt |
4.23KB |
| 10. Installing R and R Studio (Mac, Linux & Windows).mp4 |
17.55MB |
| 10. Installing R and R Studio (Mac, Linux & Windows).vtt |
7.94KB |
| 10. Logistic Regression in R - Step 2.mp4 |
7.85MB |
| 10. Logistic Regression in R - Step 2.vtt |
3.92KB |
| 10. Multiple Linear Regression in Python - Step 2.mp4 |
7.23MB |
| 10. Multiple Linear Regression in Python - Step 2.vtt |
3.63KB |
| 10. Natural Language Processing in Python - Step 7.mp4 |
17.10MB |
| 10. Natural Language Processing in Python - Step 7.vtt |
8.60KB |
| 10. Polynomial Regression in R - Step 3.mp4 |
43.31MB |
| 10. Polynomial Regression in R - Step 3.vtt |
27.44KB |
| 10. Simple Linear Regression in R - Step 2.mp4 |
14.36MB |
| 10. Simple Linear Regression in R - Step 2.vtt |
8.00KB |
| 10. Upper Confidence Bound in R - Step 3.mp4 |
47.20MB |
| 10. Upper Confidence Bound in R - Step 3.vtt |
21.98KB |
| 11. And here is our Data Preprocessing Template!.mp4 |
19.67MB |
| 11. And here is our Data Preprocessing Template!.vtt |
12.67KB |
| 11. BONUS Meet your instructors.html |
1.04KB |
| 11. HC in R - Step 2.mp4 |
11.15MB |
| 11. HC in R - Step 2.vtt |
7.32KB |
| 11. Installing Keras.html |
1.42KB |
| 11. Installing Keras.html |
927B |
| 11. Logistic Regression in R - Step 3.mp4 |
14.59MB |
| 11. Logistic Regression in R - Step 3.vtt |
6.65KB |
| 11. Multiple Linear Regression in Python - Step 3.mp4 |
14.29MB |
| 11. Multiple Linear Regression in Python - Step 3.vtt |
7.38KB |
| 11. Natural Language Processing in Python - Step 8.mp4 |
39.48MB |
| 11. Natural Language Processing in Python - Step 8.vtt |
20.80KB |
| 11. Polynomial Regression in R - Step 4.mp4 |
22.34MB |
| 11. Polynomial Regression in R - Step 4.vtt |
22.36MB |
| 11. Simple Linear Regression in R - Step 3.mp4 |
8.64MB |
| 11. Simple Linear Regression in R - Step 3.vtt |
4.94KB |
| 11. Upper Confidence Bound in R - Step 4.mp4 |
7.41MB |
| 11. Upper Confidence Bound in R - Step 4.vtt |
3.86KB |
| 12. ANN in Python - Step 1.mp4 |
29.31MB |
| 12. ANN in Python - Step 1.vtt |
17.41KB |
| 12. CNN in Python - Step 1.mp4 |
24.93MB |
| 12. CNN in Python - Step 1.vtt |
16.16KB |
| 12. Data Preprocessing.html |
118B |
| 12. HC in R - Step 3.mp4 |
7.81MB |
| 12. HC in R - Step 3.vtt |
4.29KB |
| 12. Logistic Regression in R - Step 4.mp4 |
6.91MB |
| 12. Logistic Regression in R - Step 4.vtt |
3.55KB |
| 12. Multiple Linear Regression in Python - Backward Elimination - Preparation.mp4 |
23.82MB |
| 12. Multiple Linear Regression in Python - Backward Elimination - Preparation.vtt |
13.13KB |
| 12. Natural Language Processing in Python - Step 9.mp4 |
14.01MB |
| 12. Natural Language Processing in Python - Step 9.vtt |
7.25KB |
| 12. R Regression Template.mp4 |
25.41MB |
| 12. R Regression Template.vtt |
16.72KB |
| 12. Simple Linear Regression in R - Step 4.mp4 |
37.37MB |
| 12. Simple Linear Regression in R - Step 4.vtt |
21.21KB |
| 12. Some Additional Resources.html |
551B |
| 13. ANN in Python - Step 2.mp4 |
48.09MB |
| 13. ANN in Python - Step 2.vtt |
24.77KB |
| 13. CNN in Python - Step 2.mp4 |
5.86MB |
| 13. CNN in Python - Step 2.vtt |
3.92KB |
| 13. FAQBot!.html |
1.76KB |
| 13. HC in R - Step 4.mp4 |
7.44MB |
| 13. HC in R - Step 4.vtt |
3.49KB |
| 13. Logistic Regression in R - Step 5.mp4 |
51.68MB |
| 13. Logistic Regression in R - Step 5.vtt |
26.00KB |
| 13. Multiple Linear Regression in Python - Backward Elimination - HOMEWORK !.mp4 |
32.59MB |
| 13. Multiple Linear Regression in Python - Backward Elimination - HOMEWORK !.vtt |
17.57KB |
| 13. Natural Language Processing in Python - Step 10.mp4 |
24.13MB |
| 13. Natural Language Processing in Python - Step 10.vtt |
12.49KB |
| 13. Simple Linear Regression.html |
118B |
| 14. ANN in Python - Step 3.mp4 |
8.38MB |
| 14. ANN in Python - Step 3.vtt |
4.62KB |
| 14. CNN in Python - Step 3.mp4 |
2.22MB |
| 14. CNN in Python - Step 3.vtt |
1.56KB |
| 14. HC in R - Step 5.mp4 |
6.89MB |
| 14. HC in R - Step 5.vtt |
3.66KB |
| 14. Homework Challenge.html |
1.37KB |
| 14. Multiple Linear Regression in Python - Backward Elimination - Homework Solution.mp4 |
27.17MB |
| 14. Multiple Linear Regression in Python - Backward Elimination - Homework Solution.vtt |
12.68KB |
| 14. R Classification Template.mp4 |
12.47MB |
| 14. R Classification Template.vtt |
6.06KB |
| 15. ANN in Python - Step 4.mp4 |
5.88MB |
| 15. ANN in Python - Step 4.vtt |
3.46KB |
| 15. CNN in Python - Step 4.mp4 |
27.18MB |
| 15. CNN in Python - Step 4.vtt |
16.89KB |
| 15. Hierarchical Clustering.html |
118B |
| 15. Logistic Regression.html |
118B |
| 15. Multiple Linear Regression in Python - Automatic Backward Elimination.html |
2.14KB |
| 15. Natural Language Processing in R - Step 1.mp4 |
40.38MB |
| 15. Natural Language Processing in R - Step 1.vtt |
40.38MB |
| 16.1 Clustering-Pros-Cons.pdf.pdf |
25.76KB |
| 16. ANN in Python - Step 5.mp4 |
29.58MB |
| 16. ANN in Python - Step 5.vtt |
17.06KB |
| 16. CNN in Python - Step 5.mp4 |
9.91MB |
| 16. CNN in Python - Step 5.vtt |
6.59KB |
| 16. Conclusion of Part 4 - Clustering.html |
516B |
| 16. Multiple Linear Regression in R - Step 1.mp4 |
17.94MB |
| 16. Multiple Linear Regression in R - Step 1.vtt |
10.50KB |
| 16. Natural Language Processing in R - Step 2.mp4 |
17.48MB |
| 16. Natural Language Processing in R - Step 2.vtt |
11.33KB |
| 17. ANN in Python - Step 6.mp4 |
7.06MB |
| 17. ANN in Python - Step 6.vtt |
4.03KB |
| 17. CNN in Python - Step 6.mp4 |
9.71MB |
| 17. CNN in Python - Step 6.vtt |
6.71KB |
| 17. Multiple Linear Regression in R - Step 2.mp4 |
25.93MB |
| 17. Multiple Linear Regression in R - Step 2.vtt |
13.83KB |
| 17. Natural Language Processing in R - Step 3.mp4 |
13.52MB |
| 17. Natural Language Processing in R - Step 3.vtt |
8.83KB |
| 18. ANN in Python - Step 7.mp4 |
8.99MB |
| 18. ANN in Python - Step 7.vtt |
5.17KB |
| 18. CNN in Python - Step 7.mp4 |
12.93MB |
| 18. CNN in Python - Step 7.vtt |
8.02KB |
| 18. Multiple Linear Regression in R - Step 3.mp4 |
10.41MB |
| 18. Multiple Linear Regression in R - Step 3.vtt |
6.29KB |
| 18. Natural Language Processing in R - Step 4.mp4 |
6.51MB |
| 18. Natural Language Processing in R - Step 4.vtt |
4.20KB |
| 19. ANN in Python - Step 8.mp4 |
18.17MB |
| 19. ANN in Python - Step 8.vtt |
18.18MB |
| 19. CNN in Python - Step 8.mp4 |
6.80MB |
| 19. CNN in Python - Step 8.vtt |
3.91KB |
| 19. Multiple Linear Regression in R - Backward Elimination - HOMEWORK !.mp4 |
39.73MB |
| 19. Multiple Linear Regression in R - Backward Elimination - HOMEWORK !.vtt |
24.57KB |
| 19. Natural Language Processing in R - Step 5.mp4 |
4.57MB |
| 19. Natural Language Processing in R - Step 5.vtt |
2.83KB |
| 2. Adjusted R-Squared Intuition.mp4 |
19.28MB |
| 2. Adjusted R-Squared Intuition.vtt |
12.99KB |
| 2. Algorithm Comparison UCB vs Thompson Sampling.mp4 |
14.09MB |
| 2. Algorithm Comparison UCB vs Thompson Sampling.vtt |
9.89KB |
| 2. BONUS Learning Paths.html |
2.37KB |
| 2. Confusion Matrix.mp4 |
8.22MB |
| 2. Confusion Matrix.vtt |
6.74KB |
| 2. Dataset + Business Problem Description.mp4 |
6.63MB |
| 2. Dataset + Business Problem Description.mp4 |
9.98MB |
| 2. Dataset + Business Problem Description.vtt |
3.71KB |
| 2. Dataset + Business Problem Description.vtt |
5.11KB |
| 2. Get the dataset.mp4 |
21.15MB |
| 2. Get the dataset.vtt |
9.39KB |
| 2. Hierarchical Clustering How Dendrograms Work.mp4 |
17.47MB |
| 2. Hierarchical Clustering How Dendrograms Work.vtt |
12.84KB |
| 2. How to get the dataset.mp4 |
11.71MB |
| 2. How to get the dataset.mp4 |
11.71MB |
| 2. How to get the dataset.mp4 |
11.72MB |
| 2. How to get the dataset.mp4 |
11.71MB |
| 2. How to get the dataset.mp4 |
11.71MB |
| 2. How to get the dataset.mp4 |
11.72MB |
| 2. How to get the dataset.mp4 |
11.72MB |
| 2. How to get the dataset.mp4 |
11.71MB |
| 2. How to get the dataset.mp4 |
11.71MB |
| 2. How to get the dataset.mp4 |
11.71MB |
| 2. How to get the dataset.mp4 |
11.71MB |
| 2. How to get the dataset.mp4 |
11.72MB |
| 2. How to get the dataset.vtt |
4.23KB |
| 2. How to get the dataset.vtt |
4.23KB |
| 2. How to get the dataset.vtt |
4.23KB |
| 2. How to get the dataset.vtt |
4.23KB |
| 2. How to get the dataset.vtt |
4.23KB |
| 2. How to get the dataset.vtt |
4.23KB |
| 2. How to get the dataset.vtt |
4.23KB |
| 2. How to get the dataset.vtt |
4.23KB |
| 2. How to get the dataset.vtt |
4.23KB |
| 2. How to get the dataset.vtt |
4.23KB |
| 2. How to get the dataset.vtt |
4.23KB |
| 2. How to get the dataset.vtt |
4.23KB |
| 2. Kernel PCA in Python.mp4 |
33.38MB |
| 2. Kernel PCA in Python.vtt |
18.79KB |
| 2. k-Fold Cross Validation in Python.mp4 |
32.83MB |
| 2. k-Fold Cross Validation in Python.vtt |
17.62KB |
| 2. K-Means Random Initialization Trap.mp4 |
15.36MB |
| 2. K-Means Random Initialization Trap.vtt |
11.61KB |
| 2. Mapping to a higher dimension.mp4 |
13.74MB |
| 2. Mapping to a higher dimension.vtt |
9.32KB |
| 2. Naive Bayes Intuition.mp4 |
27.79MB |
| 2. Naive Bayes Intuition.vtt |
20.89KB |
| 2. Natural Language Processing Intuition.mp4 |
29.69MB |
| 2. Natural Language Processing Intuition.vtt |
6.26KB |
| 2. SVR Intuition.mp4 |
46.59MB |
| 2. SVR Intuition.vtt |
10.11KB |
| 2. The Neuron.mp4 |
29.87MB |
| 2. The Neuron.vtt |
21.91KB |
| 2. Upper Confidence Bound (UCB) Intuition.mp4 |
29.33MB |
| 2. Upper Confidence Bound (UCB) Intuition.vtt |
29.33MB |
| 2. What are convolutional neural networks.mp4 |
29.50MB |
| 2. What are convolutional neural networks.vtt |
19.34KB |
| 2. What is Deep Learning.mp4 |
31.31MB |
| 2. What is Deep Learning.vtt |
15.89KB |
| 2. XGBoost in Python - Step 1.mp4 |
21.39MB |
| 2. XGBoost in Python - Step 1.vtt |
12.05KB |
| 20. ANN in Python - Step 9.mp4 |
16.90MB |
| 20. ANN in Python - Step 9.vtt |
8.24KB |
| 20. CNN in Python - Step 9.mp4 |
46.85MB |
| 20. CNN in Python - Step 9.vtt |
25.49KB |
| 20. Multiple Linear Regression in R - Backward Elimination - Homework Solution.mp4 |
17.24MB |
| 20. Multiple Linear Regression in R - Backward Elimination - Homework Solution.vtt |
10.59KB |
| 20. Natural Language Processing in R - Step 6.mp4 |
12.74MB |
| 20. Natural Language Processing in R - Step 6.vtt |
7.32KB |
| 21. ANN in Python - Step 10.mp4 |
17.09MB |
| 21. ANN in Python - Step 10.vtt |
9.03KB |
| 21. CNN in Python - Step 10.mp4 |
20.60MB |
| 21. CNN in Python - Step 10.vtt |
11.28KB |
| 21. Multiple Linear Regression in R - Automatic Backward Elimination.html |
726B |
| 21. Natural Language Processing in R - Step 7.mp4 |
7.52MB |
| 21. Natural Language Processing in R - Step 7.vtt |
4.99KB |
| 22. ANN in R - Step 1.mp4 |
38.55MB |
| 22. ANN in R - Step 1.vtt |
23.03KB |
| 22. CNN in R.html |
2.38KB |
| 22. Multiple Linear Regression.html |
118B |
| 22. Natural Language Processing in R - Step 8.mp4 |
13.27MB |
| 22. Natural Language Processing in R - Step 8.vtt |
6.97KB |
| 23. ANN in R - Step 2.mp4 |
14.17MB |
| 23. ANN in R - Step 2.vtt |
8.85KB |
| 23. Natural Language Processing in R - Step 9.mp4 |
28.99MB |
| 23. Natural Language Processing in R - Step 9.vtt |
17.18KB |
| 24. ANN in R - Step 3.mp4 |
28.94MB |
| 24. ANN in R - Step 3.vtt |
16.38KB |
| 24. Natural Language Processing in R - Step 10.mp4 |
41.19MB |
| 24. Natural Language Processing in R - Step 10.vtt |
22.89KB |
| 25. ANN in R - Step 4 (Last step).mp4 |
33.44MB |
| 25. ANN in R - Step 4 (Last step).vtt |
17.95KB |
| 25. Homework Challenge.html |
1.40KB |
| 3.1 Eclat.zip.zip |
48.54KB |
| 3. Accuracy Paradox.mp4 |
3.80MB |
| 3. Accuracy Paradox.vtt |
2.94KB |
| 3. Apriori in R - Step 1.mp4 |
42.87MB |
| 3. Apriori in R - Step 1.vtt |
42.89MB |
| 3. Decision Tree Classification in Python.mp4 |
29.80MB |
| 3. Decision Tree Classification in Python.vtt |
17.21KB |
| 3. Decision Tree Regression in Python.mp4 |
33.54MB |
| 3. Decision Tree Regression in Python.vtt |
21.13KB |
| 3. Eclat in R.mp4 |
20.68MB |
| 3. Eclat in R.vtt |
14.11KB |
| 3. Evaluating Regression Models Performance - Homework's Final Part.mp4 |
21.89MB |
| 3. Evaluating Regression Models Performance - Homework's Final Part.vtt |
11.59KB |
| 3. Hierarchical Clustering Using Dendrograms.mp4 |
22.81MB |
| 3. Hierarchical Clustering Using Dendrograms.vtt |
15.86KB |
| 3. How to get the dataset.mp4 |
11.71MB |
| 3. How to get the dataset.mp4 |
11.72MB |
| 3. How to get the dataset.mp4 |
11.71MB |
| 3. How to get the dataset.vtt |
4.23KB |
| 3. How to get the dataset.vtt |
4.23KB |
| 3. How to get the dataset.vtt |
4.23KB |
| 3. Importing the Libraries.mp4 |
11.08MB |
| 3. Importing the Libraries.vtt |
6.98KB |
| 3. Kernel PCA in R.mp4 |
56.57MB |
| 3. Kernel PCA in R.vtt |
26.63KB |
| 3. k-Fold Cross Validation in R.mp4 |
43.63MB |
| 3. k-Fold Cross Validation in R.vtt |
24.24KB |
| 3. K-Means Selecting The Number Of Clusters.mp4 |
23.13MB |
| 3. K-Means Selecting The Number Of Clusters.vtt |
16.55KB |
| 3. K-NN in Python.mp4 |
35.21MB |
| 3. K-NN in Python.vtt |
18.76KB |
| 3. LDA in Python.mp4 |
45.42MB |
| 3. LDA in Python.vtt |
23.05KB |
| 3. Logistic Regression in Python - Step 1.mp4 |
12.93MB |
| 3. Logistic Regression in Python - Step 1.vtt |
2.26MB |
| 3. Multiple Linear Regression Intuition - Step 1.mp4 |
1.82MB |
| 3. Multiple Linear Regression Intuition - Step 1.vtt |
1.43KB |
| 3. Naive Bayes Intuition (Challenge Reveal).mp4 |
13.28MB |
| 3. Naive Bayes Intuition (Challenge Reveal).vtt |
8.57KB |
| 3. PCA in Python - Step 1.mp4 |
31.96MB |
| 3. PCA in Python - Step 1.vtt |
15.42KB |
| 3. Polynomial Regression in Python - Step 1.mp4 |
24.89MB |
| 3. Polynomial Regression in Python - Step 1.vtt |
15.69KB |
| 3. Random Forest Classification in Python.mp4 |
47.15MB |
| 3. Random Forest Classification in Python.vtt |
27.43KB |
| 3. Random Forest Regression in Python.mp4 |
39.47MB |
| 3. Random Forest Regression in Python.vtt |
24.45KB |
| 3. Simple Linear Regression Intuition - Step 1.mp4 |
9.48MB |
| 3. Simple Linear Regression Intuition - Step 1.vtt |
7.50KB |
| 3. Step 1 - Convolution Operation.mp4 |
31.02MB |
| 3. Step 1 - Convolution Operation.vtt |
20.41KB |
| 3. SVM in Python.mp4 |
31.16MB |
| 3. SVM in Python.vtt |
16.91KB |
| 3. SVR in Python.mp4 |
46.18MB |
| 3. SVR in Python.vtt |
27.45KB |
| 3. The Activation Function.mp4 |
14.76MB |
| 3. The Activation Function.vtt |
10.56KB |
| 3. The Kernel Trick.mp4 |
29.28MB |
| 3. The Kernel Trick.vtt |
14.43KB |
| 3. Why Machine Learning is the Future.mp4 |
12.81MB |
| 3. Why Machine Learning is the Future.vtt |
8.12KB |
| 3. XGBoost in Python - Step 2.mp4 |
31.98MB |
| 3. XGBoost in Python - Step 2.vtt |
32.00MB |
| 4.1 SVM.zip.zip |
8.27KB |
| 4. Apriori in R - Step 2.mp4 |
30.50MB |
| 4. Apriori in R - Step 2.vtt |
20.59KB |
| 4. CAP Curve.mp4 |
18.68MB |
| 4. CAP Curve.vtt |
14.55KB |
| 4. Decision Tree Classification in R.mp4 |
51.18MB |
| 4. Decision Tree Classification in R.vtt |
25.86KB |
| 4. Decision Tree Regression in R.mp4 |
44.37MB |
| 4. Decision Tree Regression in R.vtt |
28.54KB |
| 4. Grid Search in Python - Step 1.mp4 |
38.21MB |
| 4. Grid Search in Python - Step 1.vtt |
19.29KB |
| 4. How do Neural Networks work.mp4 |
23.53MB |
| 4. How do Neural Networks work.vtt |
16.84KB |
| 4. How to get the dataset.mp4 |
11.71MB |
| 4. How to get the dataset.mp4 |
11.72MB |
| 4. How to get the dataset.vtt |
4.23KB |
| 4. How to get the dataset.vtt |
4.23KB |
| 4. Important notes, tips & tricks for this course.html |
3.24KB |
| 4. Importing the Dataset.mp4 |
23.31MB |
| 4. Importing the Dataset.vtt |
16.59KB |
| 4. Interpreting Linear Regression Coefficients.mp4 |
24.21MB |
| 4. Interpreting Linear Regression Coefficients.vtt |
12.02KB |
| 4. K-NN in R.mp4 |
41.37MB |
| 4. K-NN in R.vtt |
20.68KB |
| 4. LDA in R.mp4 |
51.29MB |
| 4. LDA in R.vtt |
25.61KB |
| 4. Logistic Regression in Python - Step 2.mp4 |
8.24MB |
| 4. Logistic Regression in Python - Step 2.vtt |
4.42KB |
| 4. Multiple Linear Regression Intuition - Step 2.mp4 |
1.78MB |
| 4. Multiple Linear Regression Intuition - Step 2.vtt |
1.34KB |
| 4. Naive Bayes Intuition (Extras).mp4 |
18.94MB |
| 4. Naive Bayes Intuition (Extras).vtt |
14.29KB |
| 4. Natural Language Processing in Python - Step 1.mp4 |
35.20MB |
| 4. Natural Language Processing in Python - Step 1.vtt |
15.95KB |
| 4. PCA in Python - Step 2.mp4 |
22.07MB |
| 4. PCA in Python - Step 2.vtt |
10.35KB |
| 4. Polynomial Regression in Python - Step 2.mp4 |
27.10MB |
| 4. Polynomial Regression in Python - Step 2.vtt |
15.33KB |
| 4. Random Forest Classification in R.mp4 |
49.39MB |
| 4. Random Forest Classification in R.vtt |
28.85KB |
| 4. Random Forest Regression in R.mp4 |
40.34MB |
| 4. Random Forest Regression in R.vtt |
25.10KB |
| 4. Simple Linear Regression Intuition - Step 2.mp4 |
5.37MB |
| 4. Simple Linear Regression Intuition - Step 2.vtt |
3.93KB |
| 4. Step 1(b) - ReLU Layer.mp4 |
14.09MB |
| 4. Step 1(b) - ReLU Layer.vtt |
8.08KB |
| 4. SVM in R.mp4 |
32.26MB |
| 4. SVM in R.vtt |
16.36KB |
| 4. SVR in R.mp4 |
25.87MB |
| 4. SVR in R.vtt |
16.61KB |
| 4. Thompson Sampling in Python - Step 1.mp4 |
43.13MB |
| 4. Thompson Sampling in Python - Step 1.vtt |
25.19KB |
| 4. Types of Kernel Functions.mp4 |
12.31MB |
| 4. Types of Kernel Functions.vtt |
4.37KB |
| 4. Upper Confidence Bound in Python - Step 1.mp4 |
31.53MB |
| 4. Upper Confidence Bound in Python - Step 1.vtt |
19.05KB |
| 4. XGBoost in R.mp4 |
47.26MB |
| 4. XGBoost in R.vtt |
22.59KB |
| 5.1 Machine_Learning_A_Z_Q_A.pdf.pdf |
2.26MB |
| 5. Apriori in R - Step 3.mp4 |
43.84MB |
| 5. Apriori in R - Step 3.vtt |
27.72KB |
| 5. CAP Curve Analysis.mp4 |
11.52MB |
| 5. CAP Curve Analysis.vtt |
8.35KB |
| 5. Conclusion of Part 2 - Regression.html |
2.91KB |
| 5. Grid Search in Python - Step 2.mp4 |
29.52MB |
| 5. Grid Search in Python - Step 2.vtt |
13.28KB |
| 5. HC in Python - Step 1.mp4 |
10.72MB |
| 5. HC in Python - Step 1.vtt |
6.79KB |
| 5. How do Neural Networks learn.mp4 |
26.55MB |
| 5. How do Neural Networks learn.vtt |
16.53KB |
| 5. How to get the dataset.mp4 |
11.71MB |
| 5. How to get the dataset.mp4 |
11.71MB |
| 5. How to get the dataset.vtt |
4.23KB |
| 5. How to get the dataset.vtt |
4.23KB |
| 5. K-Means Clustering in Python.mp4 |
39.77MB |
| 5. K-Means Clustering in Python.vtt |
25.22KB |
| 5. K-Nearest Neighbor.html |
118B |
| 5. Logistic Regression in Python - Step 3.mp4 |
5.98MB |
| 5. Logistic Regression in Python - Step 3.vtt |
3.66KB |
| 5. Multiple Linear Regression Intuition - Step 3.mp4 |
14.28MB |
| 5. Multiple Linear Regression Intuition - Step 3.vtt |
9.71KB |
| 5. Natural Language Processing in Python - Step 2.mp4 |
21.96MB |
| 5. Natural Language Processing in Python - Step 2.vtt |
13.74KB |
| 5. PCA in Python - Step 3.mp4 |
25.51MB |
| 5. PCA in Python - Step 3.vtt |
12.94KB |
| 5. Polynomial Regression in Python - Step 3.mp4 |
42.98MB |
| 5. Polynomial Regression in Python - Step 3.vtt |
42.99MB |
| 5. Simple Linear Regression in Python - Step 1.mp4 |
21.72MB |
| 5. Simple Linear Regression in Python - Step 1.vtt |
13.88KB |
| 5. Step 2 - Pooling.mp4 |
40.24MB |
| 5. Step 2 - Pooling.vtt |
18.41KB |
| 5. THANK YOU bonus video.mp4 |
52.24MB |
| 5. THANK YOU bonus video.vtt |
2.04KB |
| 5. This PDF resource will help you a lot.html |
1.49KB |
| 5. Thompson Sampling in Python - Step 2.mp4 |
8.42MB |
| 5. Thompson Sampling in Python - Step 2.vtt |
5.20KB |
| 5. Upper Confidence Bound in Python - Step 2.mp4 |
35.44MB |
| 5. Upper Confidence Bound in Python - Step 2.vtt |
21.82KB |
| 6.1 Machine_Learning_A-Z_New.zip.zip |
228.44MB |
| 6. Apriori in Python - Step 1.mp4 |
37.97MB |
| 6. Apriori in Python - Step 1.vtt |
24.86KB |
| 6. Conclusion of Part 3 - Classification.html |
3.75KB |
| 6. Gradient Descent.mp4 |
18.54MB |
| 6. Gradient Descent.vtt |
12.26KB |
| 6. Grid Search in R.mp4 |
35.54MB |
| 6. Grid Search in R.vtt |
18.26KB |
| 6. HC in Python - Step 2.mp4 |
12.64MB |
| 6. HC in Python - Step 2.vtt |
8.57KB |
| 6. Kernel SVM in Python.mp4 |
41.62MB |
| 6. Kernel SVM in Python.vtt |
24.98KB |
| 6. K-Means Clustering in R.mp4 |
28.99MB |
| 6. K-Means Clustering in R.vtt |
17.34KB |
| 6. Logistic Regression in Python - Step 4.mp4 |
10.38MB |
| 6. Logistic Regression in Python - Step 4.vtt |
6.37KB |
| 6. Missing Data.mp4 |
32.16MB |
| 6. Missing Data.vtt |
19.43KB |
| 6. Multiple Linear Regression Intuition - Step 4.mp4 |
4.51MB |
| 6. Multiple Linear Regression Intuition - Step 4.vtt |
3.17KB |
| 6. Naive Bayes in Python.mp4 |
23.38MB |
| 6. Naive Bayes in Python.vtt |
12.22KB |
| 6. Natural Language Processing in Python - Step 3.mp4 |
3.39MB |
| 6. Natural Language Processing in Python - Step 3.vtt |
3.39MB |
| 6. PCA in R - Step 1.mp4 |
30.65MB |
| 6. PCA in R - Step 1.vtt |
16.36KB |
| 6. Polynomial Regression in Python - Step 4.mp4 |
13.50MB |
| 6. Polynomial Regression in Python - Step 4.vtt |
13.52MB |
| 6. Simple Linear Regression in Python - Step 2.mp4 |
18.75MB |
| 6. Simple Linear Regression in Python - Step 2.vtt |
11.12KB |
| 6. Step 3 - Flattening.mp4 |
3.28MB |
| 6. Step 3 - Flattening.vtt |
2.28KB |
| 6. The whole code folder of the course.html |
1.02KB |
| 6. Thompson Sampling in R - Step 1.mp4 |
40.93MB |
| 6. Thompson Sampling in R - Step 1.vtt |
24.31KB |
| 6. Upper Confidence Bound in Python - Step 3.mp4 |
41.11MB |
| 6. Upper Confidence Bound in Python - Step 3.vtt |
23.38KB |
| 7. Apriori in Python - Step 2.mp4 |
29.52MB |
| 7. Apriori in Python - Step 2.vtt |
20.11KB |
| 7. Categorical Data.mp4 |
40.79MB |
| 7. Categorical Data.vtt |
23.86KB |
| 7. HC in Python - Step 3.mp4 |
12.30MB |
| 7. HC in Python - Step 3.vtt |
6.95KB |
| 7. Kernel SVM in R.mp4 |
40.45MB |
| 7. Kernel SVM in R.vtt |
22.66KB |
| 7. K-Means Clustering.html |
118B |
| 7. Logistic Regression in Python - Step 5.mp4 |
42.55MB |
| 7. Logistic Regression in Python - Step 5.vtt |
26.48KB |
| 7. Naive Bayes in R.mp4 |
37.31MB |
| 7. Naive Bayes in R.vtt |
19.45KB |
| 7. Natural Language Processing in Python - Step 4.mp4 |
24.01MB |
| 7. Natural Language Processing in Python - Step 4.vtt |
15.17KB |
| 7. PCA in R - Step 2.mp4 |
29.02MB |
| 7. PCA in R - Step 2.vtt |
14.64KB |
| 7. Prerequisites What is the P-Value.html |
676B |
| 7. Python Regression Template.mp4 |
27.43MB |
| 7. Python Regression Template.vtt |
14.67KB |
| 7. Simple Linear Regression in Python - Step 3.mp4 |
15.61MB |
| 7. Simple Linear Regression in Python - Step 3.vtt |
8.89KB |
| 7. Step 4 - Full Connection.mp4 |
42.75MB |
| 7. Step 4 - Full Connection.vtt |
25.08KB |
| 7. Stochastic Gradient Descent.mp4 |
16.83MB |
| 7. Stochastic Gradient Descent.vtt |
10.74KB |
| 7. Thompson Sampling in R - Step 2.mp4 |
7.47MB |
| 7. Thompson Sampling in R - Step 2.vtt |
4.76KB |
| 7. Updates on Udemy Reviews.mp4 |
52.92MB |
| 7. Updates on Udemy Reviews.vtt |
52.93MB |
| 7. Upper Confidence Bound in Python - Step 4.mp4 |
9.13MB |
| 7. Upper Confidence Bound in Python - Step 4.vtt |
4.38KB |
| 8. Apriori in Python - Step 3.mp4 |
26.96MB |
| 8. Apriori in Python - Step 3.vtt |
26.98MB |
| 8. Backpropagation.mp4 |
10.92MB |
| 8. Backpropagation.vtt |
6.32KB |
| 8. HC in Python - Step 4.mp4 |
12.02MB |
| 8. HC in Python - Step 4.vtt |
5.85KB |
| 8. Installing Python and Anaconda (Mac, Linux & Windows).mp4 |
19.52MB |
| 8. Installing Python and Anaconda (Mac, Linux & Windows).vtt |
10.98KB |
| 8. Multiple Linear Regression Intuition - Step 5.mp4 |
28.83MB |
| 8. Multiple Linear Regression Intuition - Step 5.vtt |
21.06KB |
| 8. Natural Language Processing in Python - Step 5.mp4 |
14.91MB |
| 8. Natural Language Processing in Python - Step 5.vtt |
9.23KB |
| 8. PCA in R - Step 3.mp4 |
36.73MB |
| 8. PCA in R - Step 3.vtt |
36.76MB |
| 8. Polynomial Regression in R - Step 1.mp4 |
17.78MB |
| 8. Polynomial Regression in R - Step 1.vtt |
12.66KB |
| 8. Python Classification Template.mp4 |
12.06MB |
| 8. Python Classification Template.vtt |
5.48KB |
| 8. Simple Linear Regression in Python - Step 4.mp4 |
30.82MB |
| 8. Simple Linear Regression in Python - Step 4.vtt |
20.04KB |
| 8. Summary.mp4 |
7.92MB |
| 8. Summary.vtt |
5.33KB |
| 8. Upper Confidence Bound in R - Step 1.mp4 |
28.05MB |
| 8. Upper Confidence Bound in R - Step 1.vtt |
17.91KB |
| 8. WARNING - Update.html |
2.86KB |
| 9. HC in Python - Step 5.mp4 |
8.39MB |
| 9. HC in Python - Step 5.vtt |
6.14KB |
| 9. How to get the dataset.mp4 |
11.71MB |
| 9. How to get the dataset.vtt |
4.23KB |
| 9. Logistic Regression in R - Step 1.mp4 |
12.59MB |
| 9. Logistic Regression in R - Step 1.vtt |
7.92KB |
| 9. Multiple Linear Regression in Python - Step 1.mp4 |
39.56MB |
| 9. Multiple Linear Regression in Python - Step 1.vtt |
21.52KB |
| 9. Natural Language Processing in Python - Step 6.mp4 |
6.49MB |
| 9. Natural Language Processing in Python - Step 6.vtt |
3.86KB |
| 9. Polynomial Regression in R - Step 2.mp4 |
23.87MB |
| 9. Polynomial Regression in R - Step 2.vtt |
13.72KB |
| 9. Simple Linear Regression in R - Step 1.mp4 |
9.54MB |
| 9. Simple Linear Regression in R - Step 1.vtt |
6.86KB |
| 9. Softmax & Cross-Entropy.mp4 |
33.23MB |
| 9. Softmax & Cross-Entropy.vtt |
22.13KB |
| 9. Splitting the Dataset into the Training set and Test set.mp4 |
39.03MB |
| 9. Splitting the Dataset into the Training set and Test set.vtt |
23.91KB |
| 9. Update Recommended Anaconda Version.html |
1.32KB |
| 9. Upper Confidence Bound in R - Step 2.mp4 |
29.02MB |
| 9. Upper Confidence Bound in R - Step 2.vtt |
19.20KB |