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文档列表

6. Project 2 Binary Data Classification with ANN/2. Binary Data Classification Step 2.mp4 177.1 MB
4. Introduction to Artificial Neural Networks (ANNs)/2. Activation Function.mp4 164.2 MB
13. Project 7 Predicting the Bank Customer Satisfaction with CNN/2. Predicting the Bank Customer Satisfaction - Step 2.mp4 149.0 MB
24. Project 12 Movie Review Classifivation with NLTK/2. Movie Review Classifivation with NLTK Step 2.mp4 146.7 MB
5. Project 1 Multiclass image classification with ANN/2. Step 2 - Data Preprocessing.mp4 142.2 MB
24. Project 12 Movie Review Classifivation with NLTK/1. Movie Review Classifivation with NLTK Step 1.mp4 137.5 MB
9. Project 3 Object Recognition in Images with CNN/3. Object Recognition in Images Step 3.mp4 134.8 MB
19. Project 11 Google Stock Price Prediction with RNN and LSTM/4. Google Stock Price Prediction with RNN and LSTM Step 4.mp4 124.1 MB
19. Project 11 Google Stock Price Prediction with RNN and LSTM/1. Google Stock Price Prediction with RNN and LSTM Step 1.mp4 115.6 MB
4. Introduction to Artificial Neural Networks (ANNs)/1. The Neuron.mp4 107.1 MB
14. Project 8 Credit Card Fraud Detection with CNN/2. Credit Card Fraud Detection with CNN - Step 2.mp4 106.6 MB
23. Basics of Natural Language Processing/6. Stop Words.mp4 103.5 MB
12. Project 6 Breast Cancer Detection with CNN/1. Breast Cancer Detection with CNN - Step 1.mp4 101.5 MB
8. Introduction to Convolutional Neural Networks (CNNs)/1. Convolutional Neural Network Part 1.mp4 101.0 MB
10. Project 4 Binary Image Classification with CNN/3. Binary Image Classification Step 3.mp4 99.9 MB
28. Crash course on Matplotlib (Data Visualization)/6. Matplotlib Part 3.mp4 95.7 MB
14. Project 8 Credit Card Fraud Detection with CNN/3. Credit Card Fraud Detection with CNN - Step 3.mp4 95.4 MB
28. Crash course on Matplotlib (Data Visualization)/1. Matplotlib Part 1 - Functional Method.mp4 95.0 MB
23. Basics of Natural Language Processing/3. Tokenization.mp4 90.8 MB
14. Project 8 Credit Card Fraud Detection with CNN/1. Credit Card Fraud Detection with CNN - Step 1.mp4 89.7 MB
13. Project 7 Predicting the Bank Customer Satisfaction with CNN/3. Predicting the Bank Customer Satisfaction - Step 3.mp4 89.6 MB
19. Project 11 Google Stock Price Prediction with RNN and LSTM/3. Google Stock Price Prediction with RNN and LSTM Step 3.mp4 87.6 MB
10. Project 4 Binary Image Classification with CNN/4. Binary Image Classification Step 4.mp4 86.4 MB
23. Basics of Natural Language Processing/4. Stemming.mp4 85.5 MB
8. Introduction to Convolutional Neural Networks (CNNs)/2. Convolutional Neural Network Part 2.mp4 85.1 MB
10. Project 4 Binary Image Classification with CNN/2. Binary Image Classification Step 2.mp4 84.2 MB
21. Transfer Learning/1. Transfer Learning Step 1.mp4 84.1 MB
13. Project 7 Predicting the Bank Customer Satisfaction with CNN/1. Predicting the Bank Customer Satisfaction - Step 1.mp4 83.8 MB
18. Project 10 Multiclass Image Classification with RNN - LSTM/2. Multiclass Image Classification with RNN - LSTM Step 2.mp4 82.3 MB
27. Crash Course on Pandas (Data Analysis)/3. DataFrames Part 1.mp4 81.8 MB
21. Transfer Learning/3. Transfer Learning Step 3.mp4 80.1 MB
5. Project 1 Multiclass image classification with ANN/5. Step 5 - Model evaluation and performance.mp4 79.4 MB
4. Introduction to Artificial Neural Networks (ANNs)/4. Gradient Descent and Back-Propagation.mp4 78.4 MB
23. Basics of Natural Language Processing/7. POS Tagging.mp4 78.0 MB
5. Project 1 Multiclass image classification with ANN/3. Step 3 - Building the Model.mp4 77.5 MB
27. Crash Course on Pandas (Data Analysis)/2. Pandas Series.mp4 73.4 MB
5. Project 1 Multiclass image classification with ANN/4. Step 4 - Training the Model.mp4 71.9 MB
23. Basics of Natural Language Processing/9. Named Entity Recognition.mp4 71.8 MB
23. Basics of Natural Language Processing/8. Chunking.mp4 71.4 MB
23. Basics of Natural Language Processing/1. Introduction to Natural Language Processing.mp4 71.3 MB
18. Project 10 Multiclass Image Classification with RNN - LSTM/3. Multiclass Image Classification with RNN - LSTM Step 3.mp4 68.1 MB
11. Project 5 Digit Recognition with CNN/2. Digit Recognition with CNN - Step 2.mp4 67.4 MB
11. Project 5 Digit Recognition with CNN/1. Digit Recognition with CNN - Step 1.mp4 67.2 MB
6. Project 2 Binary Data Classification with ANN/3. Binary Data Classification Step 3.mp4 66.3 MB
17. Project 9 IMDB Review Classification with RNN - LSTM/3. IMDB Review Classification with RNN - LSTM Step 3.mp4 65.9 MB
11. Project 5 Digit Recognition with CNN/3. Digit Recognition with CNN - Step 3.mp4 65.6 MB
13. Project 7 Predicting the Bank Customer Satisfaction with CNN/4. Predicting the Bank Customer Satisfaction - Step 4.mp4 65.6 MB
14. Project 8 Credit Card Fraud Detection with CNN/4. Credit Card Fraud Detection with CNN - Step 4.mp4 64.7 MB
16. Introduction to Recurrent Neural Networks/3. LSTM and GRU.mp4 62.8 MB
17. Project 9 IMDB Review Classification with RNN - LSTM/1. IMDB Review Classification with RNN - LSTM Step 1.mp4 61.5 MB
21. Transfer Learning/2. Transfer Learning Step 2.mp4 60.7 MB
27. Crash Course on Pandas (Data Analysis)/8. Merging, Joining and Concatenating DataFrames.mp4 60.0 MB
12. Project 6 Breast Cancer Detection with CNN/2. Breast Cancer Detection with CNN - Step 2.mp4 59.7 MB
27. Crash Course on Pandas (Data Analysis)/5. DataFrames Part 3.mp4 59.2 MB
9. Project 3 Object Recognition in Images with CNN/2. Object Recognition in Images Step 2.mp4 58.8 MB
6. Project 2 Binary Data Classification with ANN/5. Binary Data Classification Step 5.mp4 58.7 MB
27. Crash Course on Pandas (Data Analysis)/4. DataFrames Part 2.mp4 58.0 MB
19. Project 11 Google Stock Price Prediction with RNN and LSTM/2. Google Stock Price Prediction with RNN and LSTM Step 2.mp4 57.3 MB
17. Project 9 IMDB Review Classification with RNN - LSTM/2. IMDB Review Classification with RNN - LSTM Step 2.mp4 56.8 MB
26. Crash Course on Numpy (Data Analysis)/3. Numpy Arrays Part 2.mp4 56.6 MB
28. Crash course on Matplotlib (Data Visualization)/4. Matplotlib Part 2 - Figure size, Aspect ratio and DPI.mp4 56.6 MB
18. Project 10 Multiclass Image Classification with RNN - LSTM/1. Multiclass Image Classification with RNN - LSTM Step 1.mp4 56.3 MB
4. Introduction to Artificial Neural Networks (ANNs)/3. Cost Function.mp4 54.3 MB
10. Project 4 Binary Image Classification with CNN/5. Binary Image Classification Step 5.mp4 53.8 MB
12. Project 6 Breast Cancer Detection with CNN/3. Breast Cancer Detection with CNN - Step 3.mp4 53.5 MB
28. Crash course on Matplotlib (Data Visualization)/5. Matplotlib Part 3.mp4 52.5 MB
27. Crash Course on Pandas (Data Analysis)/7. Groupby Method.mp4 51.5 MB
21. Transfer Learning/4. Transfer Learning Step 4.mp4 50.1 MB
9. Project 3 Object Recognition in Images with CNN/5. Object Recognition in Images Step 5.mp4 50.1 MB
19. Project 11 Google Stock Price Prediction with RNN and LSTM/6. Introduction to Transfer Learning.mp4 49.8 MB
27. Crash Course on Pandas (Data Analysis)/10. Reading and Writing Files in Pandas.mp4 48.7 MB
26. Crash Course on Numpy (Data Analysis)/5. Numpy Indexing and Selection Part 1.mp4 47.3 MB
28. Crash course on Matplotlib (Data Visualization)/2. Matplotlib Part 1 - Object Oriented Method.mp4 46.1 MB
16. Introduction to Recurrent Neural Networks/1. Introduction to Recurrent Neural Networks.mp4 41.5 MB
16. Introduction to Recurrent Neural Networks/2. Vanishing Gradient Problem.mp4 40.8 MB
2. Installation and Setup/1. Introduction to Google Colab.mp4 40.8 MB
27. Crash Course on Pandas (Data Analysis)/9. Pandas Operations.mp4 40.7 MB
9. Project 3 Object Recognition in Images with CNN/4. Object Recognition in Images Step 4.mp4 40.4 MB
28. Crash course on Matplotlib (Data Visualization)/3. Matplotlib Part 2 - Subplots Method.mp4 39.6 MB
27. Crash Course on Pandas (Data Analysis)/6. Missing Data.mp4 37.0 MB
23. Basics of Natural Language Processing/5. Lemmatization.mp4 33.1 MB
5. Project 1 Multiclass image classification with ANN/1. Step 1 - Installation and Setup.mp4 33.0 MB
23. Basics of Natural Language Processing/2. NLTK Introduction and Installation.mp4 31.3 MB
26. Crash Course on Numpy (Data Analysis)/7. Numpy Operations.mp4 30.7 MB
26. Crash Course on Numpy (Data Analysis)/4. Numpy Arrays Part 3.mp4 28.6 MB
26. Crash Course on Numpy (Data Analysis)/6. Numpy Indexing and Selection Part 2.mp4 27.9 MB
19. Project 11 Google Stock Price Prediction with RNN and LSTM/5. Google Stock Price Prediction with RNN and LSTM Step 5.mp4 23.1 MB
6. Project 2 Binary Data Classification with ANN/1. Binary Data Classification Step 1.mp4 22.4 MB
1. Introduction/1. Course Introduction.mp4 22.0 MB
6. Project 2 Binary Data Classification with ANN/4. Binary Data Classification Step 4.mp4 20.1 MB
26. Crash Course on Numpy (Data Analysis)/2. Numpy Arrays Part 1.mp4 17.6 MB
10. Project 4 Binary Image Classification with CNN/1. Binary Image Classification Step 1.mp4 17.4 MB
26. Crash Course on Numpy (Data Analysis)/1. Introduction to NumPy.mp4 17.0 MB
27. Crash Course on Pandas (Data Analysis)/1. Pandas Introduction.mp4 13.1 MB
9. Project 3 Object Recognition in Images with CNN/1. Object Recognition in Images Step 1.mp4 11.2 MB
1. Introduction/2. Updates on Udemy Reviews.mp4 8.6 MB
6. Project 2 Binary Data Classification with ANN/2. Binary Data Classification Step 2-en_US.srt 26.3 kB
5. Project 1 Multiclass image classification with ANN/2. Step 2 - Data Preprocessing-en_US.srt 22.5 kB
13. Project 7 Predicting the Bank Customer Satisfaction with CNN/2. Predicting the Bank Customer Satisfaction - Step 2-en_US.srt 21.0 kB
19. Project 11 Google Stock Price Prediction with RNN and LSTM/4. Google Stock Price Prediction with RNN and LSTM Step 4-en_US.srt 19.1 kB
14. Project 8 Credit Card Fraud Detection with CNN/2. Credit Card Fraud Detection with CNN - Step 2-en_US.srt 15.8 kB
19. Project 11 Google Stock Price Prediction with RNN and LSTM/1. Google Stock Price Prediction with RNN and LSTM Step 1-en_US.srt 14.6 kB
24. Project 12 Movie Review Classifivation with NLTK/1. Movie Review Classifivation with NLTK Step 1-en_US.srt 14.2 kB
10. Project 4 Binary Image Classification with CNN/3. Binary Image Classification Step 3-en_US.srt 13.9 kB
9. Project 3 Object Recognition in Images with CNN/3. Object Recognition in Images Step 3-en_US.srt 13.9 kB
27. Crash Course on Pandas (Data Analysis)/3. DataFrames Part 1-en_US.srt 12.9 kB
19. Project 11 Google Stock Price Prediction with RNN and LSTM/3. Google Stock Price Prediction with RNN and LSTM Step 3-en_US.srt 12.5 kB
14. Project 8 Credit Card Fraud Detection with CNN/3. Credit Card Fraud Detection with CNN - Step 3-en_US.srt 12.4 kB
27. Crash Course on Pandas (Data Analysis)/2. Pandas Series-en_US.srt 11.8 kB
28. Crash course on Matplotlib (Data Visualization)/1. Matplotlib Part 1 - Functional Method-en_US.srt 11.7 kB
12. Project 6 Breast Cancer Detection with CNN/1. Breast Cancer Detection with CNN - Step 1-en_US.srt 11.6 kB
24. Project 12 Movie Review Classifivation with NLTK/2. Movie Review Classifivation with NLTK Step 2-en_US.srt 11.6 kB
18. Project 10 Multiclass Image Classification with RNN - LSTM/2. Multiclass Image Classification with RNN - LSTM Step 2-en_US.srt 11.5 kB
6. Project 2 Binary Data Classification with ANN/3. Binary Data Classification Step 3-en_US.srt 11.4 kB
13. Project 7 Predicting the Bank Customer Satisfaction with CNN/3. Predicting the Bank Customer Satisfaction - Step 3-en_US.srt 11.3 kB
5. Project 1 Multiclass image classification with ANN/3. Step 3 - Building the Model-en_US.srt 11.2 kB
27. Crash Course on Pandas (Data Analysis)/4. DataFrames Part 2-en_US.srt 11.1 kB
10. Project 4 Binary Image Classification with CNN/4. Binary Image Classification Step 4-en_US.srt 10.9 kB
21. Transfer Learning/1. Transfer Learning Step 1-en_US.srt 10.5 kB
26. Crash Course on Numpy (Data Analysis)/3. Numpy Arrays Part 2-en_US.srt 10.4 kB
27. Crash Course on Pandas (Data Analysis)/5. DataFrames Part 3-en_US.srt 10.4 kB
5. Project 1 Multiclass image classification with ANN/4. Step 4 - Training the Model-en_US.srt 10.3 kB
28. Crash course on Matplotlib (Data Visualization)/6. Matplotlib Part 3-en_US.srt 10.2 kB
5. Project 1 Multiclass image classification with ANN/5. Step 5 - Model evaluation and performance-en_US.srt 10.1 kB
10. Project 4 Binary Image Classification with CNN/2. Binary Image Classification Step 2-en_US.srt 9.9 kB
13. Project 7 Predicting the Bank Customer Satisfaction with CNN/1. Predicting the Bank Customer Satisfaction - Step 1-en_US.srt 9.6 kB
11. Project 5 Digit Recognition with CNN/1. Digit Recognition with CNN - Step 1-en_US.srt 9.6 kB
21. Transfer Learning/3. Transfer Learning Step 3-en_US.srt 9.6 kB
14. Project 8 Credit Card Fraud Detection with CNN/1. Credit Card Fraud Detection with CNN - Step 1-en_US.srt 9.5 kB
4. Introduction to Artificial Neural Networks (ANNs)/2. Activation Function-en_US.srt 9.4 kB
18. Project 10 Multiclass Image Classification with RNN - LSTM/3. Multiclass Image Classification with RNN - LSTM Step 3-en_US.srt 9.3 kB
19. Project 11 Google Stock Price Prediction with RNN and LSTM/2. Google Stock Price Prediction with RNN and LSTM Step 2-en_US.srt 9.3 kB
9. Project 3 Object Recognition in Images with CNN/2. Object Recognition in Images Step 2-en_US.srt 9.1 kB
27. Crash Course on Pandas (Data Analysis)/8. Merging, Joining and Concatenating DataFrames-en_US.srt 9.0 kB
18. Project 10 Multiclass Image Classification with RNN - LSTM/1. Multiclass Image Classification with RNN - LSTM Step 1-en_US.srt 8.9 kB
17. Project 9 IMDB Review Classification with RNN - LSTM/3. IMDB Review Classification with RNN - LSTM Step 3-en_US.srt 8.6 kB
27. Crash Course on Pandas (Data Analysis)/9. Pandas Operations-en_US.srt 8.6 kB
17. Project 9 IMDB Review Classification with RNN - LSTM/2. IMDB Review Classification with RNN - LSTM Step 2-en_US.srt 8.5 kB
27. Crash Course on Pandas (Data Analysis)/10. Reading and Writing Files in Pandas-en_US.srt 8.5 kB
14. Project 8 Credit Card Fraud Detection with CNN/4. Credit Card Fraud Detection with CNN - Step 4-en_US.srt 8.4 kB
11. Project 5 Digit Recognition with CNN/2. Digit Recognition with CNN - Step 2-en_US.srt 8.4 kB
6. Project 2 Binary Data Classification with ANN/5. Binary Data Classification Step 5-en_US.srt 8.4 kB
21. Transfer Learning/2. Transfer Learning Step 2-en_US.srt 8.4 kB
27. Crash Course on Pandas (Data Analysis)/7. Groupby Method-en_US.srt 8.3 kB
23. Basics of Natural Language Processing/6. Stop Words-en_US.srt 8.2 kB
23. Basics of Natural Language Processing/3. Tokenization-en_US.srt 8.2 kB
26. Crash Course on Numpy (Data Analysis)/5. Numpy Indexing and Selection Part 1-en_US.srt 8.0 kB
11. Project 5 Digit Recognition with CNN/3. Digit Recognition with CNN - Step 3-en_US.srt 7.9 kB
28. Crash course on Matplotlib (Data Visualization)/4. Matplotlib Part 2 - Figure size, Aspect ratio and DPI-en_US.srt 7.9 kB
12. Project 6 Breast Cancer Detection with CNN/2. Breast Cancer Detection with CNN - Step 2-en_US.srt 7.9 kB
23. Basics of Natural Language Processing/4. Stemming-en_US.srt 7.8 kB
17. Project 9 IMDB Review Classification with RNN - LSTM/1. IMDB Review Classification with RNN - LSTM Step 1-en_US.srt 7.7 kB
9. Project 3 Object Recognition in Images with CNN/5. Object Recognition in Images Step 5-en_US.srt 7.4 kB
27. Crash Course on Pandas (Data Analysis)/6. Missing Data-en_US.srt 7.3 kB
13. Project 7 Predicting the Bank Customer Satisfaction with CNN/4. Predicting the Bank Customer Satisfaction - Step 4-en_US.srt 7.2 kB
28. Crash course on Matplotlib (Data Visualization)/2. Matplotlib Part 1 - Object Oriented Method-en_US.srt 7.0 kB
23. Basics of Natural Language Processing/7. POS Tagging-en_US.srt 6.9 kB
23. Basics of Natural Language Processing/9. Named Entity Recognition-en_US.srt 6.8 kB
4. Introduction to Artificial Neural Networks (ANNs)/1. The Neuron-en_US.srt 6.7 kB
10. Project 4 Binary Image Classification with CNN/5. Binary Image Classification Step 5-en_US.srt 6.6 kB
21. Transfer Learning/4. Transfer Learning Step 4-en_US.srt 6.5 kB
23. Basics of Natural Language Processing/8. Chunking-en_US.srt 6.3 kB
12. Project 6 Breast Cancer Detection with CNN/3. Breast Cancer Detection with CNN - Step 3-en_US.srt 6.0 kB
28. Crash course on Matplotlib (Data Visualization)/3. Matplotlib Part 2 - Subplots Method-en_US.srt 5.7 kB
28. Crash course on Matplotlib (Data Visualization)/5. Matplotlib Part 3-en_US.srt 5.6 kB
9. Project 3 Object Recognition in Images with CNN/4. Object Recognition in Images Step 4-en_US.srt 5.6 kB
8. Introduction to Convolutional Neural Networks (CNNs)/1. Convolutional Neural Network Part 1-en_US.srt 5.5 kB
2. Installation and Setup/1. Introduction to Google Colab-en_US.srt 5.2 kB
8. Introduction to Convolutional Neural Networks (CNNs)/2. Convolutional Neural Network Part 2-en_US.srt 4.9 kB
26. Crash Course on Numpy (Data Analysis)/4. Numpy Arrays Part 3-en_US.srt 4.9 kB
23. Basics of Natural Language Processing/1. Introduction to Natural Language Processing-en_US.srt 4.9 kB
26. Crash Course on Numpy (Data Analysis)/6. Numpy Indexing and Selection Part 2-en_US.srt 4.9 kB
5. Project 1 Multiclass image classification with ANN/1. Step 1 - Installation and Setup-en_US.srt 4.7 kB
4. Introduction to Artificial Neural Networks (ANNs)/4. Gradient Descent and Back-Propagation-en_US.srt 4.3 kB
16. Introduction to Recurrent Neural Networks/3. LSTM and GRU-en_US.srt 4.1 kB
19. Project 11 Google Stock Price Prediction with RNN and LSTM/5. Google Stock Price Prediction with RNN and LSTM Step 5-en_US.srt 4.0 kB
26. Crash Course on Numpy (Data Analysis)/7. Numpy Operations-en_US.srt 3.9 kB
19. Project 11 Google Stock Price Prediction with RNN and LSTM/6. Introduction to Transfer Learning-en_US.srt 3.9 kB
23. Basics of Natural Language Processing/5. Lemmatization-en_US.srt 3.8 kB
26. Crash Course on Numpy (Data Analysis)/2. Numpy Arrays Part 1-en_US.srt 3.8 kB
23. Basics of Natural Language Processing/2. NLTK Introduction and Installation-en_US.srt 3.7 kB
1. Introduction/1. Course Introduction-en_US.srt 3.4 kB
4. Introduction to Artificial Neural Networks (ANNs)/3. Cost Function-en_US.srt 3.1 kB
6. Project 2 Binary Data Classification with ANN/1. Binary Data Classification Step 1-en_US.srt 3.0 kB
5. Project 1 Multiclass image classification with ANN/Imp Lecture (don't skip).html 2.7 kB
6. Project 2 Binary Data Classification with ANN/4. Binary Data Classification Step 4-en_US.srt 2.6 kB
16. Introduction to Recurrent Neural Networks/2. Vanishing Gradient Problem-en_US.srt 2.3 kB
16. Introduction to Recurrent Neural Networks/1. Introduction to Recurrent Neural Networks-en_US.srt 2.3 kB
10. Project 4 Binary Image Classification with CNN/1. Binary Image Classification Step 1-en_US.srt 2.2 kB
1. Introduction/2. Updates on Udemy Reviews-en_US.srt 1.6 kB
9. Project 3 Object Recognition in Images with CNN/1. Object Recognition in Images Step 1-en_US.srt 1.5 kB
1. Introduction/Course FAQs.html 1.2 kB
16. Introduction to Recurrent Neural Networks/Course FAQs.html 1.2 kB
4. Introduction to Artificial Neural Networks (ANNs)/Course FAQs.html 1.2 kB
8. Introduction to Convolutional Neural Networks (CNNs)/Course FAQs.html 1.2 kB
26. Crash Course on Numpy (Data Analysis)/1. Introduction to NumPy-en_US.srt 1.0 kB
2. Installation and Setup/Google Colab Update (Don't Skip).html 816 Bytes
27. Crash Course on Pandas (Data Analysis)/1. Pandas Introduction-en_US.srt 772 Bytes
22. --------------------Part 5 Natural Language Processing--------------------/Welcome to Part 5 Natural Language Processing.html 336 Bytes
2. Installation and Setup/Colab notebooks and datasets.html 299 Bytes
20. --------------------Part 4 Transfer Learning--------------------/Welcome to Part 4 - Transfer Learning.html 296 Bytes
0. Websites you may like/[Tutorialsplanet.NET].url 128 Bytes
13. Project 7 Predicting the Bank Customer Satisfaction with CNN/[Tutorialsplanet.NET].url 128 Bytes
15. --------------------Part 3 Recurrent Neural Networks (RNNs)--------------------/[Tutorialsplanet.NET].url 128 Bytes
19. Project 11 Google Stock Price Prediction with RNN and LSTM/[Tutorialsplanet.NET].url 128 Bytes
20. --------------------Part 4 Transfer Learning--------------------/[Tutorialsplanet.NET].url 128 Bytes
21. Transfer Learning/[Tutorialsplanet.NET].url 128 Bytes
22. --------------------Part 5 Natural Language Processing--------------------/[Tutorialsplanet.NET].url 128 Bytes
25. ----------------Part 6 Data Analysis and Data Visualization--------------------/[Tutorialsplanet.NET].url 128 Bytes
28. Crash course on Matplotlib (Data Visualization)/[Tutorialsplanet.NET].url 128 Bytes
4. Introduction to Artificial Neural Networks (ANNs)/[Tutorialsplanet.NET].url 128 Bytes
9. Project 3 Object Recognition in Images with CNN/[Tutorialsplanet.NET].url 128 Bytes
[Tutorialsplanet.NET].url 128 Bytes
15. --------------------Part 3 Recurrent Neural Networks (RNNs)--------------------/Welcome to Part 3 - Recurrent Neural Networks (RNNs).html 0 Bytes
25. ----------------Part 6 Data Analysis and Data Visualization--------------------/Welcome to Part 6 - Data Analysis and Data Visualization.html 0 Bytes
3. -------------------Part 1 Artificial Neural Networks (ANNs)--------------------/Welcome to Part 1 - Artificial Neural Networks (ANNs).html 0 Bytes
7. ----------------Part 2 Convolutional Neural Networks (CNNs)--------------------/Welcome to Part 2 - Convolutional Neural Networks (CNNs).html 0 Bytes

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