[Udemy] Deep Learning Recurrent Neural Networks in Python (06.2021)

Creation Time	July 31, 2023, 1:36 p.m.
Last Access Time	Nov. 16, 2024, 5:48 a.m.
File Size	3.7 GB
Keywords	06 Neural Python Recurrent Deep Udemy 2021 Learning in Networks
Total Requests	144
Total Files	150
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10. Setting Up Your Environment (FAQ by Student Request)/1. Windows-Focused Environment Setup 2018.mp4 308.9 MB
10. Setting Up Your Environment (FAQ by Student Request)/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 192.0 MB
5. Recurrent Neural Networks, Time Series, and Sequence Data/12. Demo of the Long Distance Problem.mp4 143.0 MB
12. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 136.3 MB
12. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 135.0 MB
11. Extra Help With Python Coding for Beginners (FAQ by Student Request)/3. Proof that using Jupyter Notebook is the same as not using it.mp4 108.4 MB
2. Google Colab/2. Uploading your own data to Google Colab.mp4 103.3 MB
5. Recurrent Neural Networks, Time Series, and Sequence Data/17. Stock Return Predictions using LSTMs (pt 3).mp4 99.3 MB
4. Feedforward Artificial Neural Networks/9. ANN for Regression.mp4 99.2 MB
5. Recurrent Neural Networks, Time Series, and Sequence Data/3. Autoregressive Linear Model for Time Series Prediction.mp4 97.9 MB
11. Extra Help With Python Coding for Beginners (FAQ by Student Request)/1. How to Code by Yourself (part 1).mp4 93.6 MB
5. Recurrent Neural Networks, Time Series, and Sequence Data/11. A More Challenging Sequence.mp4 88.2 MB
5. Recurrent Neural Networks, Time Series, and Sequence Data/7. RNN for Time Series Prediction.mp4 86.2 MB
3. Machine Learning and Neurons/5. Classification Notebook.mp4 77.6 MB
5. Recurrent Neural Networks, Time Series, and Sequence Data/8. Paying Attention to Shapes.mp4 76.2 MB
6. Natural Language Processing (NLP)/4. Text Classification with LSTMs.mp4 75.6 MB
2. Google Colab/1. Intro to Google Colab, how to use a GPU or TPU for free.mp4 71.6 MB
5. Recurrent Neural Networks, Time Series, and Sequence Data/1. Sequence Data.mp4 66.5 MB
3. Machine Learning and Neurons/11. How does a model learn.mp4 60.6 MB
12. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 60.2 MB
4. Feedforward Artificial Neural Networks/4. Activation Functions.mp4 59.5 MB
4. Feedforward Artificial Neural Networks/8. ANN for Image Classification.mp4 58.9 MB
5. Recurrent Neural Networks, Time Series, and Sequence Data/15. Stock Return Predictions using LSTMs (pt 1).mp4 58.3 MB
8. In-Depth Gradient Descent/5. Adam (pt 1).mp4 55.1 MB
5. Recurrent Neural Networks, Time Series, and Sequence Data/9. GRU and LSTM (pt 1).mp4 55.1 MB
8. In-Depth Gradient Descent/6. Adam (pt 2).mp4 52.8 MB
5. Recurrent Neural Networks, Time Series, and Sequence Data/5. Recurrent Neural Networks.mp4 52.0 MB
3. Machine Learning and Neurons/8. Regression Notebook.mp4 48.9 MB
3. Machine Learning and Neurons/2. What is Machine Learning.mp4 47.7 MB
1. Welcome/3. How to Succeed in this Course.mp4 46.8 MB
3. Machine Learning and Neurons/10. The Neuron.mp4 45.4 MB
4. Feedforward Artificial Neural Networks/6. How to Represent Images.mp4 43.1 MB
3. Machine Learning and Neurons/13. Saving and Loading a Model.mp4 41.7 MB
6. Natural Language Processing (NLP)/2. Code Preparation (NLP).mp4 40.9 MB
13. Appendix FAQ Finale/2. BONUS Where to get Udemy coupons and FREE deep learning material.mp4 37.8 MB
3. Machine Learning and Neurons/3. Code Preparation (Classification Theory).mp4 37.7 MB
6. Natural Language Processing (NLP)/1. Embeddings.mp4 32.9 MB
1. Welcome/2. Where to get the Code.mp4 32.5 MB
4. Feedforward Artificial Neural Networks/7. Code Preparation (ANN).mp4 32.3 MB
5. Recurrent Neural Networks, Time Series, and Sequence Data/14. RNN for Image Classification (Code).mp4 31.9 MB
1. Welcome/1. Introduction and Outline.mp4 31.5 MB
4. Feedforward Artificial Neural Networks/5. Multiclass Classification.mp4 30.8 MB
11. Extra Help With Python Coding for Beginners (FAQ by Student Request)/2. How to Code by Yourself (part 2).mp4 29.3 MB
5. Recurrent Neural Networks, Time Series, and Sequence Data/10. GRU and LSTM (pt 2).mp4 29.2 MB
4. Feedforward Artificial Neural Networks/3. The Geometrical Picture.mp4 28.7 MB
5. Recurrent Neural Networks, Time Series, and Sequence Data/16. Stock Return Predictions using LSTMs (pt 2).mp4 27.5 MB
6. Natural Language Processing (NLP)/3. Text Preprocessing.mp4 26.4 MB
5. Recurrent Neural Networks, Time Series, and Sequence Data/2. Forecasting.mp4 26.2 MB
8. In-Depth Gradient Descent/3. Momentum.mp4 25.6 MB
4. Feedforward Artificial Neural Networks/2. Forward Propagation.mp4 25.6 MB
12. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/1. How to Succeed in this Course (Long Version).mp4 24.9 MB
7. In-Depth Loss Functions/1. Mean Squared Error.mp4 24.0 MB
3. Machine Learning and Neurons/12. Making Predictions.mp4 23.6 MB
8. In-Depth Gradient Descent/4. Variable and Adaptive Learning Rates.mp4 23.5 MB
2. Google Colab/3. Where can I learn about Numpy, Scipy, Matplotlib, Pandas, and Scikit-Learn.mp4 23.4 MB
8. In-Depth Gradient Descent/1. Gradient Descent.mp4 20.8 MB
7. In-Depth Loss Functions/3. Categorical Cross Entropy.mp4 19.6 MB
3. Machine Learning and Neurons/14. Suggestion Box.mp4 19.3 MB
4. Feedforward Artificial Neural Networks/1. Artificial Neural Networks Section Introduction.mp4 18.4 MB
8. In-Depth Gradient Descent/2. Stochastic Gradient Descent.mp4 18.2 MB
5. Recurrent Neural Networks, Time Series, and Sequence Data/13. RNN for Image Classification (Theory).mp4 18.1 MB
3. Machine Learning and Neurons/7. Code Preparation (Regression Theory).mp4 16.8 MB
5. Recurrent Neural Networks, Time Series, and Sequence Data/18. Other Ways to Forecast.mp4 15.9 MB
3. Machine Learning and Neurons/4. Beginner's Code Preamble.mp4 13.7 MB
7. In-Depth Loss Functions/2. Binary Cross Entropy.mp4 12.8 MB
3. Machine Learning and Neurons/6. Exercise Predicting Diabetes Onset.mp4 12.6 MB
5. Recurrent Neural Networks, Time Series, and Sequence Data/6. RNN Code Preparation.mp4 11.7 MB
4. Feedforward Artificial Neural Networks/10. Exercise E. Coli Protein Localization Sites.mp4 10.5 MB
11. Extra Help With Python Coding for Beginners (FAQ by Student Request)/4. Python 2 vs Python 3.mp4 10.4 MB
5. Recurrent Neural Networks, Time Series, and Sequence Data/4. Proof that the Linear Model Works.mp4 9.9 MB
6. Natural Language Processing (NLP)/5. Exercise Sentiment Analysis.mp4 9.1 MB
13. Appendix FAQ Finale/1. What is the Appendix.mp4 8.9 MB
3. Machine Learning and Neurons/1. Review Section Introduction.mp4 7.5 MB
3. Machine Learning and Neurons/9. Exercise Real Estate Predictions.mp4 5.6 MB
12. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced-en_US.srt 30.7 KB
5. Recurrent Neural Networks, Time Series, and Sequence Data/5. Recurrent Neural Networks-en_US.srt 24.7 KB
5. Recurrent Neural Networks, Time Series, and Sequence Data/1. Sequence Data-en_US.srt 23.1 KB
12. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/4. Machine Learning and AI Prerequisite Roadmap (pt 2)-en_US.srt 22.7 KB
5. Recurrent Neural Networks, Time Series, and Sequence Data/12. Demo of the Long Distance Problem-en_US.srt 22.3 KB
4. Feedforward Artificial Neural Networks/4. Activation Functions-en_US.srt 22.1 KB
11. Extra Help With Python Coding for Beginners (FAQ by Student Request)/1. How to Code by Yourself (part 1)-en_US.srt 21.7 KB
5. Recurrent Neural Networks, Time Series, and Sequence Data/9. GRU and LSTM (pt 1)-en_US.srt 20.0 KB
3. Machine Learning and Neurons/3. Code Preparation (Classification Theory)-en_US.srt 19.7 KB
10. Setting Up Your Environment (FAQ by Student Request)/1. Windows-Focused Environment Setup 2018-en_US.srt 19.0 KB
3. Machine Learning and Neurons/2. What is Machine Learning-en_US.srt 18.2 KB
6. Natural Language Processing (NLP)/2. Code Preparation (NLP)-en_US.srt 16.2 KB
8. In-Depth Gradient Descent/5. Adam (pt 1)-en_US.srt 16.1 KB
12. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/3. Machine Learning and AI Prerequisite Roadmap (pt 1)-en_US.srt 16.0 KB
6. Natural Language Processing (NLP)/1. Embeddings-en_US.srt 15.9 KB
4. Feedforward Artificial Neural Networks/7. Code Preparation (ANN)-en_US.srt 15.8 KB
5. Recurrent Neural Networks, Time Series, and Sequence Data/15. Stock Return Predictions using LSTMs (pt 1)-en_US.srt 15.3 KB
4. Feedforward Artificial Neural Networks/6. How to Represent Images-en_US.srt 15.3 KB
8. In-Depth Gradient Descent/4. Variable and Adaptive Learning Rates-en_US.srt 14.6 KB
5. Recurrent Neural Networks, Time Series, and Sequence Data/10. GRU and LSTM (pt 2)-en_US.srt 14.2 KB
12. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/1. How to Succeed in this Course (Long Version)-en_US.srt 14.2 KB
5. Recurrent Neural Networks, Time Series, and Sequence Data/17. Stock Return Predictions using LSTMs (pt 3)-en_US.srt 14.0 KB
5. Recurrent Neural Networks, Time Series, and Sequence Data/3. Autoregressive Linear Model for Time Series Prediction-en_US.srt 13.9 KB
8. In-Depth Gradient Descent/6. Adam (pt 2)-en_US.srt 13.9 KB
3. Machine Learning and Neurons/11. How does a model learn-en_US.srt 13.7 KB
10. Setting Up Your Environment (FAQ by Student Request)/2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow-en_US.srt 13.6 KB
2. Google Colab/1. Intro to Google Colab, how to use a GPU or TPU for free-en_US.srt 13.6 KB
11. Extra Help With Python Coding for Beginners (FAQ by Student Request)/3. Proof that using Jupyter Notebook is the same as not using it-en_US.srt 13.5 KB
4. Feedforward Artificial Neural Networks/9. ANN for Regression-en_US.srt 12.8 KB
11. Extra Help With Python Coding for Beginners (FAQ by Student Request)/2. How to Code by Yourself (part 2)-en_US.srt 12.8 KB
5. Recurrent Neural Networks, Time Series, and Sequence Data/2. Forecasting-en_US.srt 12.2 KB
3. Machine Learning and Neurons/10. The Neuron-en_US.srt 12.1 KB
4. Feedforward Artificial Neural Networks/2. Forward Propagation-en_US.srt 11.9 KB
1. Welcome/2. Where to get the Code-en_US.srt 11.9 KB
3. Machine Learning and Neurons/8. Regression Notebook-en_US.srt 11.9 KB
2. Google Colab/2. Uploading your own data to Google Colab-en_US.srt 11.5 KB
4. Feedforward Artificial Neural Networks/3. The Geometrical Picture-en_US.srt 11.3 KB
7. In-Depth Loss Functions/1. Mean Squared Error-en_US.srt 11.0 KB
2. Google Colab/3. Where can I learn about Numpy, Scipy, Matplotlib, Pandas, and Scikit-Learn-en_US.srt 10.9 KB
4. Feedforward Artificial Neural Networks/5. Multiclass Classification-en_US.srt 10.7 KB
5. Recurrent Neural Networks, Time Series, and Sequence Data/7. RNN for Time Series Prediction-en_US.srt 10.7 KB
5. Recurrent Neural Networks, Time Series, and Sequence Data/8. Paying Attention to Shapes-en_US.srt 9.6 KB
4. Feedforward Artificial Neural Networks/8. ANN for Image Classification-en_US.srt 9.5 KB
6. Natural Language Processing (NLP)/4. Text Classification with LSTMs-en_US.srt 9.5 KB
8. In-Depth Gradient Descent/1. Gradient Descent-en_US.srt 9.5 KB
7. In-Depth Loss Functions/3. Categorical Cross Entropy-en_US.srt 9.4 KB
5. Recurrent Neural Networks, Time Series, and Sequence Data/11. A More Challenging Sequence-en_US.srt 9.3 KB
3. Machine Learning and Neurons/5. Classification Notebook-en_US.srt 8.9 KB
3. Machine Learning and Neurons/7. Code Preparation (Regression Theory)-en_US.srt 8.5 KB
1. Welcome/3. How to Succeed in this Course-en_US.srt 7.9 KB
3. Machine Learning and Neurons/12. Making Predictions-en_US.srt 7.8 KB
4. Feedforward Artificial Neural Networks/1. Artificial Neural Networks Section Introduction-en_US.srt 7.7 KB
13. Appendix FAQ Finale/2. BONUS Where to get Udemy coupons and FREE deep learning material-en_US.srt 7.5 KB
8. In-Depth Gradient Descent/3. Momentum-en_US.srt 7.5 KB
5. Recurrent Neural Networks, Time Series, and Sequence Data/18. Other Ways to Forecast-en_US.srt 7.0 KB
7. In-Depth Loss Functions/2. Binary Cross Entropy-en_US.srt 6.9 KB
5. Recurrent Neural Networks, Time Series, and Sequence Data/6. RNN Code Preparation-en_US.srt 6.9 KB
3. Machine Learning and Neurons/4. Beginner's Code Preamble-en_US.srt 6.6 KB
5. Recurrent Neural Networks, Time Series, and Sequence Data/16. Stock Return Predictions using LSTMs (pt 2)-en_US.srt 6.3 KB
6. Natural Language Processing (NLP)/3. Text Preprocessing-en_US.srt 6.0 KB
11. Extra Help With Python Coding for Beginners (FAQ by Student Request)/4. Python 2 vs Python 3-en_US.srt 5.8 KB
5. Recurrent Neural Networks, Time Series, and Sequence Data/13. RNN for Image Classification (Theory)-en_US.srt 5.6 KB
8. In-Depth Gradient Descent/2. Stochastic Gradient Descent-en_US.srt 5.3 KB
3. Machine Learning and Neurons/13. Saving and Loading a Model-en_US.srt 4.7 KB
3. Machine Learning and Neurons/14. Suggestion Box-en_US.srt 4.5 KB
5. Recurrent Neural Networks, Time Series, and Sequence Data/14. RNN for Image Classification (Code)-en_US.srt 4.5 KB
5. Recurrent Neural Networks, Time Series, and Sequence Data/4. Proof that the Linear Model Works-en_US.srt 4.4 KB
1. Welcome/1. Introduction and Outline-en_US.srt 4.4 KB
9. Extras/Colab Notebooks.html 4.0 KB
13. Appendix FAQ Finale/1. What is the Appendix-en_US.srt 3.7 KB
3. Machine Learning and Neurons/1. Review Section Introduction-en_US.srt 3.5 KB
3. Machine Learning and Neurons/6. Exercise Predicting Diabetes Onset-en_US.srt 3.1 KB
4. Feedforward Artificial Neural Networks/10. Exercise E. Coli Protein Localization Sites-en_US.srt 2.8 KB
6. Natural Language Processing (NLP)/5. Exercise Sentiment Analysis-en_US.srt 2.5 KB
3. Machine Learning and Neurons/9. Exercise Real Estate Predictions-en_US.srt 1.6 KB
1. Welcome/2. External URLs.txt 75 bytes

[Udemy] Deep Learning Recurrent Neural Networks in Python (06.2021)

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