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| [CourseClub.Me].url |
122B |
| [CourseClub.Me].url |
122B |
| [CourseClub.Me].url |
122B |
| [CourseClub.Me].url |
122B |
| [CourseClub.Me].url |
122B |
| [GigaCourse.Com].url |
49B |
| [GigaCourse.Com].url |
49B |
| [GigaCourse.Com].url |
49B |
| [GigaCourse.Com].url |
49B |
| [GigaCourse.Com].url |
49B |
| 001 [Activity] Linear Regression_en.srt |
23.77KB |
| 001 [Activity] Linear Regression.mp4 |
92.96MB |
| 001 [Activity] The OpenAI Chat Completions API_en.srt |
24.86KB |
| 001 [Activity] The OpenAI Chat Completions API.mp4 |
70.44MB |
| 001 BiasVariance Tradeoff_en.srt |
12.77KB |
| 001 BiasVariance Tradeoff.mp4 |
23.63MB |
| 001 Chat-Completions.py |
1.15KB |
| 001 Deep Learning Pre-Requisites_en.srt |
26.05KB |
| 001 Deep Learning Pre-Requisites.mp4 |
70.40MB |
| 001 Deploying Models to Real-Time Systems_en.srt |
18.76KB |
| 001 Deploying Models to Real-Time Systems.mp4 |
17.22MB |
| 001 Introduction_en.srt |
6.09KB |
| 001 Introduction.mp4 |
59.57MB |
| 001 K-Nearest-Neighbors Concepts_en.srt |
7.87KB |
| 001 K-Nearest-Neighbors Concepts.mp4 |
14.04MB |
| 001 More to Explore_en.srt |
6.82KB |
| 001 More to Explore.mp4 |
33.99MB |
| 001 Retrieval Augmented Generation (RAG) How it works, with some examples_en.srt |
37.23KB |
| 001 Retrieval Augmented Generation (RAG) How it works, with some examples.mp4 |
92.89MB |
| 001 Supervised vs. Unsupervised Learning, and TrainTest_en.srt |
19.41KB |
| 001 Supervised vs. Unsupervised Learning, and TrainTest.mp4 |
56.68MB |
| 001 The Transformer Architecture (encoders, decoders, and self-attention.)_en.srt |
22.26KB |
| 001 The Transformer Architecture (encoders, decoders, and self-attention.).mp4 |
44.20MB |
| 001 Types of Data (Numerical, Categorical, Ordinal)_en.srt |
14.44KB |
| 001 Types of Data (Numerical, Categorical, Ordinal).mp4 |
73.10MB |
| 001 User-Based Collaborative Filtering_en.srt |
17.34KB |
| 001 User-Based Collaborative Filtering.mp4 |
81.69MB |
| 001 Variational Auto-Encoders (VAE's) - how they work_en.srt |
21.64KB |
| 001 Variational Auto-Encoders (VAE's) - how they work.mp4 |
42.88MB |
| 001 Warning about Java 21+ and Spark 3!.html |
389B |
| 001 Your final project assignment Mammogram Classification_en.srt |
14.35KB |
| 001 Your final project assignment Mammogram Classification.mp4 |
51.60MB |
| 002 [Activity] K-Fold Cross-Validation to avoid overfitting_en.srt |
20.62KB |
| 002 [Activity] K-Fold Cross-Validation to avoid overfitting.mp4 |
56.90MB |
| 002 [Activity] Polynomial Regression_en.srt |
15.75KB |
| 002 [Activity] Polynomial Regression.mp4 |
60.55MB |
| 002 [Activity] Using KNN to predict a rating for a movie_en.srt |
24.10KB |
| 002 [Activity] Using KNN to predict a rating for a movie.mp4 |
85.54MB |
| 002 [Activity] Using Tools and Functions in the OpenAI Chat Completion API_en.srt |
19.08KB |
| 002 [Activity] Using Tools and Functions in the OpenAI Chat Completion API.mp4 |
61.23MB |
| 002 [Activity] Using TrainTest to Prevent Overfitting a Polynomial Regression_en.srt |
11.93KB |
| 002 [Activity] Using TrainTest to Prevent Overfitting a Polynomial Regression.mp4 |
21.62MB |
| 002 AB Testing Concepts_en.srt |
18.69KB |
| 002 AB Testing Concepts.mp4 |
32.02MB |
| 002 Data-RAG.ipynb |
100.43KB |
| 002 Demo Using Retrieval Augmented Generation (RAG) to simulate Data from Star Trek_en.srt |
40.71KB |
| 002 Demo Using Retrieval Augmented Generation (RAG) to simulate Data from Star Trek.mp4 |
184.47MB |
| 002 Don't Forget to Leave a Rating!.html |
564B |
| 002 Final project review_en.srt |
22.27KB |
| 002 Final project review.mp4 |
64.49MB |
| 002 Functions.py |
3.45KB |
| 002 Item-Based Collaborative Filtering_en.srt |
17.78KB |
| 002 Item-Based Collaborative Filtering.mp4 |
23.20MB |
| 002 Mean, Median, Mode_en.srt |
11.58KB |
| 002 Mean, Median, Mode.mp4 |
15.96MB |
| 002 Self-Attention, Masked Self-Attention, and Multi-Headed Self Attention in depth_en.srt |
21.69KB |
| 002 Self-Attention, Masked Self-Attention, and Multi-Headed Self Attention in depth.mp4 |
41.50MB |
| 002 Spark installation notes for MacOS and Linux users.html |
3.10KB |
| 002 The History of Artificial Neural Networks_en.srt |
24.16KB |
| 002 The History of Artificial Neural Networks.mp4 |
68.87MB |
| 002 Udemy 101 Getting the Most From This Course_en.srt |
4.91KB |
| 002 Udemy 101 Getting the Most From This Course.mp4 |
17.40MB |
| 002 VariationalAutoEncoders.ipynb |
1.33MB |
| 002 Variational Auto-Encoders (VAE) - Hands-on with Fashion MNIST_en.srt |
54.65KB |
| 002 Variational Auto-Encoders (VAE) - Hands-on with Fashion MNIST.mp4 |
148.84MB |
| 003 [Activity] Deep Learning in the Tensorflow Playground_en.srt |
23.97KB |
| 003 [Activity] Deep Learning in the Tensorflow Playground.mp4 |
55.69MB |
| 003 [Activity] Finding Movie Similarities using Cosine Similarity_en.srt |
17.87KB |
| 003 [Activity] Finding Movie Similarities using Cosine Similarity.mp4 |
82.67MB |
| 003 [Activity] Installing Spark_en.srt |
21.27KB |
| 003 [Activity] Installing Spark.mp4 |
141.36MB |
| 003 [Activity] Multiple Regression, and Predicting Car Prices_en.srt |
34.22KB |
| 003 [Activity] Multiple Regression, and Predicting Car Prices.mp4 |
94.14MB |
| 003 [Activity] The Images (DALL-E) API in OpenAI_en.srt |
8.80KB |
| 003 [Activity] The Images (DALL-E) API in OpenAI.mp4 |
29.59MB |
| 003 [Activity] Using mean, median, and mode in Python_en.srt |
19.31KB |
| 003 [Activity] Using mean, median, and mode in Python.mp4 |
44.50MB |
| 003 Applications of Transformers (GPT)_en.srt |
10.10KB |
| 003 Applications of Transformers (GPT).mp4 |
20.19MB |
| 003 Bayesian Methods Concepts_en.srt |
8.11KB |
| 003 Bayesian Methods Concepts.mp4 |
9.83MB |
| 003 Bonus Lecture.html |
9.23KB |
| 003 Data Cleaning and Normalization_en.srt |
16.18KB |
| 003 Data Cleaning and Normalization.mp4 |
73.09MB |
| 003 Dimensionality Reduction; Principal Component Analysis (PCA)_en.srt |
11.67KB |
| 003 Dimensionality Reduction; Principal Component Analysis (PCA).mp4 |
38.13MB |
| 003 Generative Adversarial Networks (GAN's) - How they work_en.srt |
15.94KB |
| 003 Generative Adversarial Networks (GAN's) - How they work.mp4 |
15.24MB |
| 003 Image.py |
664B |
| 003 Important note.html |
575B |
| 003 T-Tests and P-Values_en.srt |
12.26KB |
| 003 T-Tests and P-Values.mp4 |
14.08MB |
| 004 [Activity] Cleaning web log data_en.srt |
21.75KB |
| 004 [Activity] Cleaning web log data.mp4 |
31.01MB |
| 004 [Activity] Hands-on With T-Tests_en.srt |
12.35KB |
| 004 [Activity] Hands-on With T-Tests.mp4 |
47.77MB |
| 004 [Activity] Implementing a Spam Classifier with Naive Bayes_en.srt |
16.58KB |
| 004 [Activity] Implementing a Spam Classifier with Naive Bayes.mp4 |
81.39MB |
| 004 [Activity] Improving the Results of Movie Similarities_en.srt |
16.22KB |
| 004 [Activity] Improving the Results of Movie Similarities.mp4 |
56.06MB |
| 004 [Activity] PCA Example with the Iris data set_en.srt |
17.94KB |
| 004 [Activity] PCA Example with the Iris data set.mp4 |
65.77MB |
| 004 [Activity] The Embeddings API in OpenAI Finding similarities between words_en.srt |
13.29KB |
| 004 [Activity] The Embeddings API in OpenAI Finding similarities between words.mp4 |
32.93MB |
| 004 [Activity] Variation and Standard Deviation_en.srt |
22.99KB |
| 004 [Activity] Variation and Standard Deviation.mp4 |
103.39MB |
| 004 Deep Learning Details_en.srt |
20.88KB |
| 004 Deep Learning Details.mp4 |
30.90MB |
| 004 Embedding.py |
964B |
| 004 Generative Adversarial Networks (GAN's) - Playing with some demos_en.srt |
21.68KB |
| 004 Generative Adversarial Networks (GAN's) - Playing with some demos.mp4 |
86.14MB |
| 004 How GPT Works, Part 1 The GPT Transformer Architecture_en.srt |
16.02KB |
| 004 How GPT Works, Part 1 The GPT Transformer Architecture.mp4 |
30.27MB |
| 004 Installation Getting Started.html |
1.21KB |
| 004 Multi-Level Models_en.srt |
9.75KB |
| 004 Multi-Level Models.mp4 |
27.22MB |
| 004 Spark Introduction_en.srt |
19.17KB |
| 004 Spark Introduction.mp4 |
24.96MB |
| 005 [Activity] Making Movie Recommendations with Item-Based Collaborative Filtering_en.srt |
20.25KB |
| 005 [Activity] Making Movie Recommendations with Item-Based Collaborative Filtering.mp4 |
124.11MB |
| 005 [Activity] WINDOWS Installing and Using Anaconda & Course Materials_en.srt |
20.70KB |
| 005 [Activity] WINDOWS Installing and Using Anaconda & Course Materials.mp4 |
101.97MB |
| 005 Data Warehousing Overview ETL and ELT_en.srt |
18.07KB |
| 005 Data Warehousing Overview ETL and ELT.mp4 |
58.71MB |
| 005 Determining How Long to Run an Experiment_en.srt |
7.70KB |
| 005 Determining How Long to Run an Experiment.mp4 |
9.75MB |
| 005 GAN-on-Fashion-MNIST.ipynb |
3.75MB |
| 005 Generative Adversarial Networks (GAN's) - Hands-on with Fashion MNIST_en.srt |
32.64KB |
| 005 Generative Adversarial Networks (GAN's) - Hands-on with Fashion MNIST.mp4 |
126.11MB |
| 005 How GPT Works, Part 2 Tokenization, Positional Encoding, Embedding_en.srt |
10.77KB |
| 005 How GPT Works, Part 2 Tokenization, Positional Encoding, Embedding.mp4 |
28.55MB |
| 005 Introducing Tensorflow_en.srt |
26.57KB |
| 005 Introducing Tensorflow.mp4 |
46.63MB |
| 005 K-Means Clustering_en.srt |
15.63KB |
| 005 K-Means Clustering.mp4 |
26.02MB |
| 005 Normalizing numerical data_en.srt |
7.17KB |
| 005 Normalizing numerical data.mp4 |
10.32MB |
| 005 Probability Density Function; Probability Mass Function_en.srt |
7.09KB |
| 005 Probability Density Function; Probability Mass Function.mp4 |
6.92MB |
| 005 Spark and the Resilient Distributed Dataset (RDD)_en.srt |
24.21KB |
| 005 Spark and the Resilient Distributed Dataset (RDD).mp4 |
22.30MB |
| 005 The Legacy Fine-Tuning API for GPT Models in OpenAI_en.srt |
11.45KB |
| 005 The Legacy Fine-Tuning API for GPT Models in OpenAI.mp4 |
29.42MB |
| 006 [Activity] Clustering people based on income and age_en.srt |
11.11KB |
| 006 [Activity] Clustering people based on income and age.mp4 |
21.99MB |
| 006 [Activity] Detecting outliers_en.srt |
13.30KB |
| 006 [Activity] Detecting outliers.mp4 |
27.15MB |
| 006 [Activity] MAC Installing and Using Anaconda & Course Materials_en.srt |
16.88KB |
| 006 [Activity] MAC Installing and Using Anaconda & Course Materials.mp4 |
96.18MB |
| 006 [Activity] Using Tensorflow, Part 1_en.srt |
27.67KB |
| 006 [Activity] Using Tensorflow, Part 1.mp4 |
107.70MB |
| 006 [Demo] Fine-Tuning OpenAI's Davinci Model to simulate Data from Star Trek_en.srt |
35.28KB |
| 006 [Demo] Fine-Tuning OpenAI's Davinci Model to simulate Data from Star Trek.mp4 |
170.75MB |
| 006 [Exercise] Improve the recommender's results_en.srt |
12.11KB |
| 006 [Exercise] Improve the recommender's results.mp4 |
28.00MB |
| 006 AB Test Gotchas_en.srt |
20.95KB |
| 006 AB Test Gotchas.mp4 |
91.73MB |
| 006 Cat-and-Mouse-Example.url |
103B |
| 006 Common Data Distributions (Normal, Binomial, Poisson, etc)_en.srt |
14.50KB |
| 006 Common Data Distributions (Normal, Binomial, Poisson, etc).mp4 |
28.25MB |
| 006 extract-script.py |
1.88KB |
| 006 Fine Tuning Transfer Learning with Transformers_en.srt |
5.49KB |
| 006 Fine Tuning Transfer Learning with Transformers.mp4 |
11.52MB |
| 006 Introducing MLLib_en.srt |
10.44KB |
| 006 Introducing MLLib.mp4 |
14.65MB |
| 006 Learning More about Deep Learning_en.srt |
3.79KB |
| 006 Learning More about Deep Learning.mp4 |
20.21MB |
| 006 Pac-Man-Example.url |
108B |
| 006 Python-Markov-Decision-Process-Toolbox.url |
82B |
| 006 Reinforcement Learning_en.srt |
25.34KB |
| 006 Reinforcement Learning.mp4 |
125.18MB |
| 007 [Activity] LINUX Installing and Using Anaconda & Course Materials_en.srt |
17.96KB |
| 007 [Activity] LINUX Installing and Using Anaconda & Course Materials.mp4 |
85.52MB |
| 007 [Activity] Percentiles and Moments_en.srt |
26.84KB |
| 007 [Activity] Percentiles and Moments.mp4 |
42.56MB |
| 007 [Activity] Reinforcement Learning & Q-Learning with Gym_en.srt |
26.58KB |
| 007 [Activity] Reinforcement Learning & Q-Learning with Gym.mp4 |
62.79MB |
| 007 [Activity] Tokenization with Google CoLab and HuggingFace_en.srt |
18.61KB |
| 007 [Activity] Tokenization with Google CoLab and HuggingFace.mp4 |
78.96MB |
| 007 [Activity] Using Tensorflow, Part 2_en.srt |
24.87KB |
| 007 [Activity] Using Tensorflow, Part 2.mp4 |
95.13MB |
| 007 Feature Engineering and the Curse of Dimensionality_en.srt |
13.94KB |
| 007 Feature Engineering and the Curse of Dimensionality.mp4 |
14.56MB |
| 007 Introduction to Decision Trees in Spark_en.srt |
33.11KB |
| 007 Introduction to Decision Trees in Spark.mp4 |
133.95MB |
| 007 MakingData.ipynb |
13.57KB |
| 007 Measuring Entropy_en.srt |
6.40KB |
| 007 Measuring Entropy.mp4 |
12.14MB |
| 007 The New OpenAI Fine-Tuning API; Fine-Tuning GPT-3.5 to simulate Commander Data!_en.srt |
45.87KB |
| 007 The New OpenAI Fine-Tuning API; Fine-Tuning GPT-3.5 to simulate Commander Data!.mp4 |
318.98MB |
| 007 Transformers-MLCourse.ipynb |
6.69MB |
| 008 [Activity] A Crash Course in matplotlib_en.srt |
26.11KB |
| 008 [Activity] A Crash Course in matplotlib.mp4 |
78.70MB |
| 008 [Activity] Introducing Keras_en.srt |
28.63KB |
| 008 [Activity] Introducing Keras.mp4 |
72.03MB |
| 008 [Activity] K-Means Clustering in Spark_en.srt |
21.09KB |
| 008 [Activity] K-Means Clustering in Spark.mp4 |
116.14MB |
| 008 [Activity] Positional Encoding_en.srt |
4.30KB |
| 008 [Activity] Positional Encoding.mp4 |
15.97MB |
| 008 [Activity] The OpenAI Moderation API.mp4 |
17.15MB |
| 008 [Activity] WINDOWS Installing Graphviz_en.srt |
872B |
| 008 [Activity] WINDOWS Installing Graphviz.mp4 |
949.28KB |
| 008 Imputation Techniques for Missing Data_en.srt |
17.31KB |
| 008 Imputation Techniques for Missing Data.mp4 |
18.20MB |
| 008 Moderation.py |
166B |
| 008 Python Basics, Part 1 [Optional]_en.srt |
9.54KB |
| 008 Python Basics, Part 1 [Optional].mp4 |
26.90MB |
| 008 Understanding a Confusion Matrix_en.srt |
11.63KB |
| 008 Understanding a Confusion Matrix.mp4 |
7.38MB |
| 009 [Activity] Advanced Visualization with Seaborn_en.srt |
35.71KB |
| 009 [Activity] Advanced Visualization with Seaborn.mp4 |
96.14MB |
| 009 [Activity] MAC Installing Graphviz_en.srt |
1.81KB |
| 009 [Activity] MAC Installing Graphviz.mp4 |
9.07MB |
| 009 [Activity] Masked, Multi-Headed Self Attention with BERT, BERTViz, and exBERT_en.srt |
12.76KB |
| 009 [Activity] Masked, Multi-Headed Self Attention with BERT, BERTViz, and exBERT.mp4 |
39.78MB |
| 009 [Activity] Python Basics, Part 2 [Optional]_en.srt |
9.30KB |
| 009 [Activity] Python Basics, Part 2 [Optional].mp4 |
20.62MB |
| 009 [Activity] The OpenAI Audio API (speech to text)_en.srt |
8.16KB |
| 009 [Activity] The OpenAI Audio API (speech to text).mp4 |
28.72MB |
| 009 [Activity] Using Keras to Predict Political Affiliations_en.srt |
25.36KB |
| 009 [Activity] Using Keras to Predict Political Affiliations.mp4 |
88.85MB |
| 009 Audio.py |
445B |
| 009 Handling Unbalanced Data Oversampling, Undersampling, and SMOTE_en.srt |
11.83KB |
| 009 Handling Unbalanced Data Oversampling, Undersampling, and SMOTE.mp4 |
17.43MB |
| 009 Measuring Classifiers (Precision, Recall, F1, ROC, AUC)_en.srt |
12.69KB |
| 009 Measuring Classifiers (Precision, Recall, F1, ROC, AUC).mp4 |
11.67MB |
| 009 TF IDF_en.srt |
13.36KB |
| 009 TF IDF.mp4 |
65.66MB |
| 010 [Activity] Covariance and Correlation_en.srt |
23.70KB |
| 010 [Activity] Covariance and Correlation.mp4 |
69.48MB |
| 010 [Activity] LINUX Installing Graphviz_en.srt |
1.37KB |
| 010 [Activity] LINUX Installing Graphviz.mp4 |
2.48MB |
| 010 [Activity] Python Basics, Part 3 [Optional]_en.srt |
5.24KB |
| 010 [Activity] Python Basics, Part 3 [Optional].mp4 |
5.14MB |
| 010 [Activity] Searching Wikipedia with Spark_en.srt |
15.61KB |
| 010 [Activity] Searching Wikipedia with Spark.mp4 |
84.01MB |
| 010 [Activity] Using small and large GPT models within Google CoLab and HuggingFace_en.srt |
10.76KB |
| 010 [Activity] Using small and large GPT models within Google CoLab and HuggingFace.mp4 |
69.34MB |
| 010 Binning, Transforming, Encoding, Scaling, and Shuffling_en.srt |
16.93KB |
| 010 Binning, Transforming, Encoding, Scaling, and Shuffling.mp4 |
42.72MB |
| 010 Convolutional Neural Networks (CNN's)_en.srt |
24.85KB |
| 010 Convolutional Neural Networks (CNN's).mp4 |
58.73MB |
| 011 [Activity] Fine Tuning GPT with the IMDb dataset_en.srt |
13.39KB |
| 011 [Activity] Fine Tuning GPT with the IMDb dataset.mp4 |
85.20MB |
| 011 [Activity] Python Basics, Part 4 [Optional]_en.srt |
7.13KB |
| 011 [Activity] Python Basics, Part 4 [Optional].mp4 |
8.19MB |
| 011 [Activity] Using CNN's for handwriting recognition_en.srt |
16.80KB |
| 011 [Activity] Using CNN's for handwriting recognition.mp4 |
52.82MB |
| 011 [Activity] Using the Spark DataFrame API for MLLib_en.srt |
15.11KB |
| 011 [Activity] Using the Spark DataFrame API for MLLib.mp4 |
65.11MB |
| 011 [Exercise] Conditional Probability_en.srt |
34.13KB |
| 011 [Exercise] Conditional Probability.mp4 |
93.95MB |
| 011 Decision Trees Concepts_en.srt |
18.68KB |
| 011 Decision Trees Concepts.mp4 |
81.50MB |
| 012 [Activity] Decision Trees Predicting Hiring Decisions_en.srt |
20.13KB |
| 012 [Activity] Decision Trees Predicting Hiring Decisions.mp4 |
57.79MB |
| 012 Exercise Solution Conditional Probability of Purchase by Age_en.srt |
4.78KB |
| 012 Exercise Solution Conditional Probability of Purchase by Age.mp4 |
15.01MB |
| 012 From GPT to ChatGPT Deep Reinforcement Learning, Proximal Policy Gradients_en.srt |
15.91KB |
| 012 From GPT to ChatGPT Deep Reinforcement Learning, Proximal Policy Gradients.mp4 |
51.12MB |
| 012 Introducing the Pandas Library [Optional]_en.srt |
21.87KB |
| 012 Introducing the Pandas Library [Optional].mp4 |
44.15MB |
| 012 Recurrent Neural Networks (RNN's)_en.srt |
22.97KB |
| 012 Recurrent Neural Networks (RNN's).mp4 |
32.81MB |
| 013 [Activity] Using a RNN for sentiment analysis_en.srt |
20.70KB |
| 013 [Activity] Using a RNN for sentiment analysis.mp4 |
73.55MB |
| 013 Bayes' Theorem_en.srt |
10.36KB |
| 013 Bayes' Theorem.mp4 |
56.12MB |
| 013 Ensemble Learning_en.srt |
12.73KB |
| 013 Ensemble Learning.mp4 |
36.96MB |
| 013 From GPT to ChatGPT Reinforcement Learning from Human Feedback and Moderation_en.srt |
12.84KB |
| 013 From GPT to ChatGPT Reinforcement Learning from Human Feedback and Moderation.mp4 |
37.75MB |
| 014 [Activity] Transfer Learning_en.srt |
25.28KB |
| 014 [Activity] Transfer Learning.mp4 |
111.05MB |
| 014 [Activity] XGBoost_en.srt |
33.72KB |
| 014 [Activity] XGBoost.mp4 |
79.28MB |
| 015 Support Vector Machines (SVM) Overview_en.srt |
9.50KB |
| 015 Support Vector Machines (SVM) Overview.mp4 |
16.35MB |
| 015 Tuning Neural Networks Learning Rate and Batch Size Hyperparameters_en.srt |
10.32KB |
| 015 Tuning Neural Networks Learning Rate and Batch Size Hyperparameters.mp4 |
8.50MB |
| 016 [Activity] Using SVM to cluster people using scikit-learn_en.srt |
20.00KB |
| 016 [Activity] Using SVM to cluster people using scikit-learn.mp4 |
38.49MB |
| 016 Deep Learning Regularization with Dropout and Early Stopping_en.srt |
13.89KB |
| 016 Deep Learning Regularization with Dropout and Early Stopping.mp4 |
19.84MB |
| 017 The Ethics of Deep Learning_en.srt |
24.95KB |
| 017 The Ethics of Deep Learning.mp4 |
120.50MB |
| external-links.txt |
325B |