Udemy Deep Learning Convolutional Neural Networks in Python 2025 | 05DF7C021B6CDC5CC56EBB4FBADE372D24B5E8E5

Udemy Deep Learning Convolutional Neural Networks in Python 2025

Name	Udemy - Deep Learning Convolutional Neural Networks in Python (5.2025)	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	4.2 GB
Total Files	162
Last Seen	2025-07-14 00:33
Hash	05DF7C021B6CDC5CC56EBB4FBADE372D24B5E8E5

/01. Welcome/
1. Introduction and Outline.mp4	7.8 MB
1. Introduction and Outline.vtt	3.3 KB
2. Code-Link.txt	0.1 KB
2. Github-Link.txt	0.1 KB
2. Where to get the code.mp4	7.1 MB
2. Where to get the code.vtt	6.1 KB
3. How to Succeed in this Course.mp4	9.4 MB
3. How to Succeed in this Course.vtt	4.0 KB
/02. Google Colab/
1. Intro to Google Colab, how to use a GPU or TPU for free.mp4	75.1 MB
1. Intro to Google Colab, how to use a GPU or TPU for free.vtt	13.0 KB
2. Uploading your own data to Google Colab.mp4	108.3 MB
2. Uploading your own data to Google Colab.vtt	11.1 KB
3. Where can I learn about Numpy, Scipy, Matplotlib, Pandas, and Scikit-Learn.mp4	38.3 MB
3. Where can I learn about Numpy, Scipy, Matplotlib, Pandas, and Scikit-Learn.vtt	13.0 KB
4. Temporary 403 Errors.mp4	33.2 MB
4. Temporary 403 Errors.vtt	3.3 KB
/03. Machine Learning and Neurons/
1. Review Section Introduction.mp4	7.9 MB
1. Review Section Introduction.vtt	3.3 KB
10. Saving and Loading a Model.mp4	43.7 MB
10. Saving and Loading a Model.vtt	4.5 KB
11. Suggestion Box.mp4	41.7 MB
11. Suggestion Box.vtt	4.2 KB
2. What is Machine Learning.mp4	50.3 MB
2. What is Machine Learning.vtt	17.1 KB
3. Code Preparation (Classification Theory).mp4	39.6 MB
3. Code Preparation (Classification Theory).vtt	18.6 KB
4. Classification Notebook.mp4	180.5 MB
4. Classification Notebook.vtt	24.1 KB
5. Code Preparation (Regression Theory).mp4	17.7 MB
5. Code Preparation (Regression Theory).vtt	8.2 KB
6. Regression Notebook.mp4	91.8 MB
6. Regression Notebook.vtt	30.3 KB
7. The Neuron.mp4	27.6 MB
7. The Neuron.vtt	11.5 KB
8. How does a model learn.mp4	63.5 MB
8. How does a model learn.vtt	12.9 KB
9. Making Predictions.mp4	24.7 MB
9. Making Predictions.vtt	7.5 KB
/04. Feedforward Artificial Neural Networks/
1. Artificial Neural Networks Section Introduction.mp4	19.3 MB
1. Artificial Neural Networks Section Introduction.vtt	7.2 KB
10. ANN for Regression.mp4	104.0 MB
10. ANN for Regression.vtt	12.0 KB
2. Forward Propagation.mp4	26.8 MB
2. Forward Propagation.vtt	11.2 KB
3. The Geometrical Picture.mp4	30.1 MB
3. The Geometrical Picture.vtt	10.7 KB
4. Activation Functions.mp4	62.4 MB
4. Activation Functions.vtt	20.4 KB
5. Multiclass Classification.mp4	32.3 MB
5. Multiclass Classification.vtt	10.1 KB
6. How to Represent Images.mp4	45.2 MB
6. How to Represent Images.vtt	14.4 KB
7. Color Mixing Clarification.mp4	2.8 MB
7. Color Mixing Clarification.vtt	1.0 KB
8. Code Preparation (ANN).mp4	33.9 MB
8. Code Preparation (ANN).vtt	14.8 KB
9. ANN for Image Classification.mp4	46.5 MB
9. ANN for Image Classification.vtt	9.2 KB
/05. Convolutional Neural Networks/
1. What is Convolution (part 1).mp4	45.5 MB
1. What is Convolution (part 1).vtt	18.6 KB
10. Data Augmentation.mp4	27.0 MB
10. Data Augmentation.vtt	10.4 KB
11. Batch Normalization.mp4	13.7 MB
11. Batch Normalization.vtt	6.1 KB
12. Improving CIFAR-10 Results (Legacy).mp4	106.1 MB
12. Improving CIFAR-10 Results (Legacy).vtt	12.1 KB
2. What is Convolution (part 2).mp4	15.2 MB
2. What is Convolution (part 2).vtt	6.5 KB
3. What is Convolution (part 3).mp4	17.0 MB
3. What is Convolution (part 3).vtt	7.2 KB
4. Why use 0-indexing.mp4	210.7 MB
4. Why use 0-indexing.vtt	20.2 KB
5. Convolution on Color Images.mp4	48.1 MB
5. Convolution on Color Images.vtt	18.8 KB
6. CNN Architecture.mp4	62.6 MB
6. CNN Architecture.vtt	25.7 KB
7. CNN Code Preparation.mp4	60.4 MB
7. CNN Code Preparation.vtt	18.1 KB
8. CNN for Fashion MNIST.mp4	40.4 MB
8. CNN for Fashion MNIST.vtt	7.3 KB
9. CNN for CIFAR-10.mp4	27.0 MB
9. CNN for CIFAR-10.vtt	5.1 KB
/06. Natural Language Processing (NLP)/
1. Embeddings.mp4	37.7 MB
1. Embeddings.vtt	15.8 KB
2. Code Preparation (NLP).mp4	46.5 MB
2. Code Preparation (NLP).vtt	16.5 KB
3. Text Preprocessing.mp4	62.3 MB
3. Text Preprocessing.vtt	21.3 KB
4. CNNs for Text.mp4	22.6 MB
4. CNNs for Text.vtt	9.1 KB
5. Text Classification with CNNs.mp4	313.4 MB
5. Text Classification with CNNs.vtt	25.1 KB
/07. Convolution In-Depth/
1. Real-Life Examples of Convolution.mp4	37.9 MB
1. Real-Life Examples of Convolution.vtt	8.0 KB
2. Beginner's Guide to Convolution.mp4	18.4 MB
2. Beginner's Guide to Convolution.vtt	7.2 KB
3. Alternative Views on Convolution.mp4	22.5 MB
3. Alternative Views on Convolution.vtt	7.6 KB
/08. Convolutional Neural Network Description/
1. Convolution on 3-D Images.mp4	22.8 MB
1. Convolution on 3-D Images.vtt	12.7 KB
2. Tracking Shapes in a CNN.mp4	38.9 MB
2. Tracking Shapes in a CNN.vtt	18.7 KB
/09. Practical Tips/
1. Advanced CNNs and how to Design your Own.mp4	39.1 MB
1. Advanced CNNs and how to Design your Own.vtt	13.6 KB
/10. In-Depth Loss Functions/
1. Mean Squared Error.mp4	25.2 MB
1. Mean Squared Error.vtt	10.4 KB
2. Binary Cross Entropy.mp4	13.4 MB
2. Binary Cross Entropy.vtt	6.6 KB
3. Categorical Cross Entropy.mp4	20.5 MB
3. Categorical Cross Entropy.vtt	9.0 KB
/11. In-Depth Gradient Descent/
1. Gradient Descent.mp4	21.8 MB
1. Gradient Descent.vtt	9.0 KB
2. Stochastic Gradient Descent.mp4	19.1 MB
2. Stochastic Gradient Descent.vtt	4.8 KB
3. Momentum.mp4	26.8 MB
3. Momentum.vtt	7.0 KB
4. Variable and Adaptive Learning Rates.mp4	24.6 MB
4. Variable and Adaptive Learning Rates.vtt	13.7 KB
5. Adam (pt 1).mp4	40.0 MB
5. Adam (pt 1).vtt	15.2 KB
6. Adam (pt 2).mp4	32.8 MB
6. Adam (pt 2).vtt	12.7 KB
/12. Appendix FAQ Intro/
1. What is the Appendix.mp4	19.2 MB
1. What is the Appendix.vtt	8.3 KB
/13. Setting Up Your Environment (FAQ by Student Request)/
1. Pre-Installation Check.mp4	13.7 MB
1. Pre-Installation Check.vtt	5.9 KB
2. Anaconda Environment Setup.mp4	324.1 MB
2. Anaconda Environment Setup.vtt	17.7 KB
3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4	201.3 MB
3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt	17.2 KB
/14. Extra Help With Python Coding for Beginners (FAQ by Student Request)/
1. Beginner's Coding Tips.mp4	44.9 MB
1. Beginner's Coding Tips.vtt	17.2 KB
10. Is Theano Dead.mp4	29.3 MB
10. Is Theano Dead.vtt	12.0 KB
2. Data-Links.txt	0.1 KB
2. Get Your Hands Dirty, Practical Coding Experience, Data Links.mp4	26.6 MB
2. Get Your Hands Dirty, Practical Coding Experience, Data Links.vtt	10.8 KB
2. Github-Link.txt	0.1 KB
3. Where To Get the Code Troubleshooting.mp4	31.1 MB
3. Where To Get the Code Troubleshooting.vtt	5.2 KB
4. How to use Github & Extra Coding Tips (Optional).mp4	46.6 MB
4. How to use Github & Extra Coding Tips (Optional).vtt	14.1 KB
5. How to Code by Yourself (part 1).mp4	98.1 MB
5. How to Code by Yourself (part 1).vtt	28.5 KB
6. How to Code by Yourself (part 2).mp4	30.7 MB
6. How to Code by Yourself (part 2).vtt	16.5 KB
7. How to Uncompress a .tar.gz file.mp4	6.7 MB
7. How to Uncompress a .tar.gz file.vtt	3.7 KB
8. Proof that using Jupyter Notebook is the same as not using it.mp4	113.7 MB
8. Proof that using Jupyter Notebook is the same as not using it.vtt	13.0 KB
9. Python 2 vs Python 3.mp4	10.9 MB
9. Python 2 vs Python 3.vtt	5.6 KB
/15. Effective Learning Strategies for Machine Learning (FAQ by Student Request)/
1. How to Succeed in this Course (Long Version).mp4	26.1 MB
1. How to Succeed in this Course (Long Version).vtt	13.4 KB
2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4	63.1 MB
2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt	29.0 KB
3. Machine Learning and AI Prerequisite Roadmap (pt 1).mp4	141.4 MB
3. Machine Learning and AI Prerequisite Roadmap (pt 1).vtt	15.0 KB
4. Machine Learning and AI Prerequisite Roadmap (pt 2).mp4	143.0 MB
4. Machine Learning and AI Prerequisite Roadmap (pt 2).vtt	21.4 KB
/16. Appendix FAQ Finale/
1. BONUS.mp4	45.3 MB
1. BONUS.vtt	7.2 KB
Total files 162