Udemy PyTorch Deep Learning and Artificial Intelligence 12 2024 | 714E6D8708DA74301C32AB737A5C05F01E77246B

Udemy PyTorch Deep Learning and Artificial Intelligence 12 2024

Name	Udemy - PyTorch Deep Learning and Artificial Intelligence (12.2024)	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	8.4 GB
Total Files	306
Last Seen	2025-08-23 00:24
Hash	714E6D8708DA74301C32AB737A5C05F01E77246B

/1 - Introduction/
1 -Welcome.mp4	37.4 MB
1 -Welcome.vtt	5.2 KB
2 -Overview and Outline.mp4	83.5 MB
2 -Overview and Outline.vtt	16.1 KB
/10 - Transfer Learning for Computer Vision/
1 -Transfer Learning Theory.mp4	60.9 MB
1 -Transfer Learning Theory.vtt	9.7 KB
2 -Some Pre-trained Models (VGG, ResNet, Inception, MobileNet).mp4	22.7 MB
2 -Some Pre-trained Models (VGG, ResNet, Inception, MobileNet).vtt	4.7 KB
3 -Large Datasets.mp4	43.2 MB
3 -Large Datasets.vtt	8.2 KB
4 -2 Approaches to Transfer Learning.mp4	22.8 MB
4 -2 Approaches to Transfer Learning.vtt	5.4 KB
5 -Transfer Learning Code (pt 1).mp4	81.6 MB
5 -Transfer Learning Code (pt 1).vtt	10.4 KB
6 -Transfer Learning Code (pt 2).mp4	59.0 MB
6 -Transfer Learning Code (pt 2).vtt	7.9 KB
/11 - GANs (Generative Adversarial Networks)/
1 -GAN Theory.mp4	96.5 MB
1 -GAN Theory.vtt	18.9 KB
2 -GAN Code Preparation.mp4	29.5 MB
2 -GAN Code Preparation.vtt	7.6 KB
3 -GAN Code.mp4	64.5 MB
3 -GAN Code.vtt	9.6 KB
/12 - Deep Reinforcement Learning (Theory)/
1 -Deep Reinforcement Learning Section Introduction.mp4	42.7 MB
1 -Deep Reinforcement Learning Section Introduction.vtt	7.7 KB
10 -Epsilon-Greedy.mp4	43.5 MB
10 -Epsilon-Greedy.vtt	6.7 KB
11 -Q-Learning.mp4	70.0 MB
11 -Q-Learning.vtt	16.0 KB
12 -Deep Q-Learning DQN (pt 1).mp4	63.0 MB
12 -Deep Q-Learning DQN (pt 1).vtt	14.7 KB
13 -Deep Q-Learning DQN (pt 2).mp4	54.6 MB
13 -Deep Q-Learning DQN (pt 2).vtt	11.9 KB
14 -How to Learn Reinforcement Learning.mp4	42.2 MB
14 -How to Learn Reinforcement Learning.vtt	6.9 KB
2 -Elements of a Reinforcement Learning Problem.mp4	110.1 MB
2 -Elements of a Reinforcement Learning Problem.vtt	23.4 KB
3 -States, Actions, Rewards, Policies.mp4	46.2 MB
3 -States, Actions, Rewards, Policies.vtt	10.2 KB
4 -Markov Decision Processes (MDPs).mp4	52.9 MB
4 -Markov Decision Processes (MDPs).vtt	11.5 KB
5 -The Return.mp4	24.5 MB
5 -The Return.vtt	5.6 KB
6 -Value Functions and the Bellman Equation.mp4	50.0 MB
6 -Value Functions and the Bellman Equation.vtt	11.2 KB
7 -What does it mean to “learn”.mp4	33.2 MB
7 -What does it mean to “learn”.vtt	8.0 KB
8 -Solving the Bellman Equation with Reinforcement Learning (pt 1).mp4	48.1 MB
8 -Solving the Bellman Equation with Reinforcement Learning (pt 1).vtt	11.5 KB
9 -Solving the Bellman Equation with Reinforcement Learning (pt 2).mp4	58.2 MB
9 -Solving the Bellman Equation with Reinforcement Learning (pt 2).vtt	13.8 KB
/13 - Stock Trading Project with Deep Reinforcement Learning/
1 -Reinforcement Learning Stock Trader Introduction.mp4	30.2 MB
1 -Reinforcement Learning Stock Trader Introduction.vtt	6.1 KB
2 -Data and Environment.mp4	58.4 MB
2 -Data and Environment.vtt	14.1 KB
3 -Replay Buffer.mp4	26.1 MB
3 -Replay Buffer.vtt	6.2 KB
4 -Program Design and Layout.mp4	28.1 MB
4 -Program Design and Layout.vtt	7.8 KB
5 -Code pt 1.mp4	69.6 MB
5 -Code pt 1.vtt	10.8 KB
6 -Code pt 2.mp4	73.4 MB
6 -Code pt 2.vtt	10.5 KB
7 -Code pt 3.mp4	61.4 MB
7 -Code pt 3.vtt	7.6 KB
8 -Code pt 4.mp4	55.1 MB
8 -Code pt 4.vtt	7.5 KB
9 -Reinforcement Learning Stock Trader Discussion.mp4	18.0 MB
9 -Reinforcement Learning Stock Trader Discussion.vtt	4.0 KB
/14 - VIP Uncertainty Estimation/
1 -Custom Loss and Estimating Prediction Uncertainty.mp4	45.6 MB
1 -Custom Loss and Estimating Prediction Uncertainty.vtt	11.5 KB
2 -Estimating Prediction Uncertainty Code.mp4	44.7 MB
2 -Estimating Prediction Uncertainty Code.vtt	7.9 KB
/15 - VIP Facial Recognition/
1 -Facial Recognition Section Introduction.mp4	25.5 MB
1 -Facial Recognition Section Introduction.vtt	4.1 KB
10 -Facial Recognition Section Summary.mp4	19.2 MB
10 -Facial Recognition Section Summary.vtt	4.0 KB
2 -Siamese Networks.mp4	52.9 MB
2 -Siamese Networks.vtt	11.5 KB
3 -Code Outline.mp4	25.0 MB
3 -Code Outline.vtt	5.2 KB
4 -Loading in the data.mp4	36.7 MB
4 -Loading in the data.vtt	6.2 KB
5 -Splitting the data into train and test.mp4	27.5 MB
5 -Splitting the data into train and test.vtt	4.6 KB
6 -Converting the data into pairs.mp4	31.8 MB
6 -Converting the data into pairs.vtt	5.3 KB
7 -Generating Generators.mp4	34.0 MB
7 -Generating Generators.vtt	5.2 KB
8 -Creating the model and loss.mp4	30.8 MB
8 -Creating the model and loss.vtt	4.8 KB
9 -Accuracy and imbalanced classes.mp4	53.6 MB
9 -Accuracy and imbalanced classes.vtt	8.6 KB
/16 - In-Depth Loss Functions/
1 -Mean Squared Error.mp4	35.4 MB
1 -Mean Squared Error.vtt	10.1 KB
2 -Binary Cross Entropy.mp4	24.8 MB
2 -Binary Cross Entropy.vtt	6.5 KB
3 -Categorical Cross Entropy.mp4	33.3 MB
3 -Categorical Cross Entropy.vtt	8.6 KB
/17 - In-Depth Gradient Descent/
1 -Gradient Descent.mp4	36.6 MB
1 -Gradient Descent.vtt	8.8 KB
2 -Stochastic Gradient Descent.mp4	24.1 MB
2 -Stochastic Gradient Descent.vtt	4.9 KB
3 -Momentum.mp4	35.9 MB
3 -Momentum.vtt	7.1 KB
4 -Variable and Adaptive Learning Rates.mp4	36.5 MB
4 -Variable and Adaptive Learning Rates.vtt	13.6 KB
5 -Adam (pt 1).mp4	57.8 MB
5 -Adam (pt 1).vtt	15.0 KB
6 -Adam (pt 2).mp4	55.3 MB
6 -Adam (pt 2).vtt	13.0 KB
/18 - Extras/
1 -Where Are The Exercises.mp4	27.2 MB
1 -Where Are The Exercises.vtt	4.9 KB
/19 - Setting up your Environment (FAQ by Student Request)/
1 -Pre-Installation Check.mp4	23.8 MB
1 -Pre-Installation Check.vtt	5.9 KB
2 -How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4	158.0 MB
2 -How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt	12.9 KB
3 -Anaconda Environment Setup.mp4	189.6 MB
3 -Anaconda Environment Setup.vtt	17.8 KB
4 -Installing NVIDIA GPU-Accelerated Deep Learning Libraries on your Home Computer.mp4	175.4 MB
4 -Installing NVIDIA GPU-Accelerated Deep Learning Libraries on your Home Computer.vtt	28.6 KB
/2 - Getting Set Up/
1 -Code Link.url	0.1 KB
1 -Data Links.url	0.1 KB
1 -Github Link.url	0.1 KB
1 -Where to get the code, notebooks, and data.mp4	28.2 MB
1 -Where to get the code, notebooks, and data.vtt	5.7 KB
2 -How to Succeed in This Course.mp4	17.0 MB
2 -How to Succeed in This Course.vtt	4.0 KB
3 -Temporary 403 Errors.mp4	23.0 MB
3 -Temporary 403 Errors.vtt	3.3 KB
/20 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/
1 -Beginner's Coding Tips.mp4	79.4 MB
1 -Beginner's Coding Tips.vtt	17.0 KB
2 -How to Code Yourself (part 1).mp4	75.3 MB
2 -How to Code Yourself (part 1).vtt	20.7 KB
3 -How to Code Yourself (part 2).mp4	51.5 MB
3 -How to Code Yourself (part 2).vtt	11.7 KB
4 -Proof that using Jupyter Notebook is the same as not using it.mp4	72.8 MB
4 -Proof that using Jupyter Notebook is the same as not using it.vtt	12.6 KB
5 -Data Links.url	0.1 KB
5 -Get Your Hands Dirty, Practical Coding Experience, Data Links.mp4	45.7 MB
5 -Get Your Hands Dirty, Practical Coding Experience, Data Links.vtt	10.8 KB
5 -Github Link.url	0.1 KB
6 -How to use Github & Extra Coding Tips (Optional).mp4	67.0 MB
6 -How to use Github & Extra Coding Tips (Optional).vtt	14.1 KB
/21 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/
1 -How to Succeed in this Course (Long Version).mp4	36.9 MB
1 -How to Succeed in this Course (Long Version).vtt	13.1 KB
2 -Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4	110.7 MB
2 -Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt	28.3 KB
3 -Machine Learning and AI Prerequisite Roadmap (pt 1).mp4	83.6 MB
3 -Machine Learning and AI Prerequisite Roadmap (pt 1).vtt	14.5 KB
4 -Machine Learning and AI Prerequisite Roadmap (pt 2).mp4	113.4 MB
4 -Machine Learning and AI Prerequisite Roadmap (pt 2).vtt	20.7 KB
/22 - Appendix FAQ Finale/
1 -What is the Appendix.mp4	17.2 MB
1 -What is the Appendix.vtt	3.4 KB
2 -BONUS.mp4	42.4 MB
2 -BONUS.vtt	7.2 KB
/3 - Google Colab/
1 -Intro to Google Colab, how to use a GPU or TPU for free.mp4	63.4 MB
1 -Intro to Google Colab, how to use a GPU or TPU for free.vtt	12.8 KB
2 -Uploading your own data to Google Colab.mp4	94.9 MB
2 -Uploading your own data to Google Colab.vtt	12.9 KB
3 -Where can I learn about Numpy, Scipy, Matplotlib, Pandas, and Scikit-Learn.mp4	59.8 MB
3 -Where can I learn about Numpy, Scipy, Matplotlib, Pandas, and Scikit-Learn.vtt	13.7 KB
/4 - Machine Learning and Neurons/
1 -What is Machine Learning.mp4	73.9 MB
1 -What is Machine Learning.vtt	16.6 KB
10 -Saving and Loading a Model.mp4	30.2 MB
10 -Saving and Loading a Model.vtt	6.0 KB
11 -A Short Neuroscience Primer.mp4	46.8 MB
11 -A Short Neuroscience Primer.vtt	11.0 KB
12 -How does a model learn.mp4	52.5 MB
12 -How does a model learn.vtt	12.4 KB
13 -Model With Logits.mp4	28.5 MB
13 -Model With Logits.vtt	4.8 KB
14 -Train Sets vs. Validation Sets vs. Test Sets.mp4	54.7 MB
14 -Train Sets vs. Validation Sets vs. Test Sets.vtt	12.8 KB
15 -Suggestion Box.mp4	28.5 MB
15 -Suggestion Box.vtt	4.2 KB
2 -Regression Basics.mp4	76.6 MB
2 -Regression Basics.vtt	17.9 KB
3 -Regression Code Preparation.mp4	47.7 MB
3 -Regression Code Preparation.vtt	14.6 KB
4 -Regression Notebook.mp4	75.4 MB
4 -Regression Notebook.vtt	15.7 KB
5 -Moore's Law.mp4	32.0 MB
5 -Moore's Law.vtt	8.2 KB
6 -Moore's Law Notebook.mp4	82.8 MB
6 -Moore's Law Notebook.vtt	14.2 KB
7 -Linear Classification Basics.mp4	69.0 MB
7 -Linear Classification Basics.vtt	18.3 KB
8 -Classification Code Preparation.mp4	27.8 MB
8 -Classification Code Preparation.vtt	8.5 KB
9 -Classification Notebook.mp4	82.1 MB
9 -Classification Notebook.vtt	13.1 KB
/5 - Feedforward Artificial Neural Networks/
1 -Artificial Neural Networks Section Introduction.mp4	35.0 MB
1 -Artificial Neural Networks Section Introduction.vtt	7.1 KB
10 -ANN for Regression.mp4	84.0 MB
10 -ANN for Regression.vtt	11.6 KB
11 -How to Choose Hyperparameters.mp4	41.4 MB
11 -How to Choose Hyperparameters.vtt	7.7 KB
2 -Forward Propagation.mp4	49.3 MB
2 -Forward Propagation.vtt	10.9 KB
3 -The Geometrical Picture.mp4	59.2 MB
3 -The Geometrical Picture.vtt	10.4 KB
4 -Activation Functions.mp4	93.6 MB
4 -Activation Functions.vtt	20.3 KB
5 -Multiclass Classification.mp4	51.0 MB
5 -Multiclass Classification.vtt	11.0 KB
6 -How to Represent Images.mp4	79.1 MB
6 -How to Represent Images.vtt	13.8 KB
7 -Color Mixing Clarification.mp4	5.1 MB
7 -Color Mixing Clarification.vtt	1.0 KB
8 -Code Preparation (ANN).mp4	69.3 MB
8 -Code Preparation (ANN).vtt	18.3 KB
9 -ANN for Image Classification.mp4	111.5 MB
9 -ANN for Image Classification.vtt	20.3 KB
/6 - Convolutional Neural Networks/
1 -What is Convolution (part 1).mp4	83.6 MB
1 -What is Convolution (part 1).vtt	18.8 KB
10 -CNN for CIFAR-10.mp4	58.0 MB
10 -CNN for CIFAR-10.vtt	8.1 KB
11 -Data Augmentation.mp4	46.6 MB
11 -Data Augmentation.vtt	11.2 KB
12 -Batch Normalization.mp4	24.5 MB
12 -Batch Normalization.vtt	5.9 KB
13 -Improving CIFAR-10 Results.mp4	79.4 MB
13 -Improving CIFAR-10 Results.vtt	11.5 KB
2 -What is Convolution (part 2).mp4	25.2 MB
2 -What is Convolution (part 2).vtt	6.5 KB
3 -What is Convolution (part 3).mp4	31.3 MB
3 -What is Convolution (part 3).vtt	7.2 KB
4 -Convolution on Color Images.mp4	79.3 MB
4 -Convolution on Color Images.vtt	18.8 KB
5 -CNN Architecture.mp4	93.8 MB
5 -CNN Architecture.vtt	24.9 KB
6 -CNN Code Preparation (part 1).mp4	83.8 MB
6 -CNN Code Preparation (part 1).vtt	22.0 KB
7 -CNN Code Preparation (part 2).mp4	38.5 MB
7 -CNN Code Preparation (part 2).vtt	9.5 KB
8 -CNN Code Preparation (part 3).mp4	35.3 MB
8 -CNN Code Preparation (part 3).vtt	6.4 KB
9 -CNN for Fashion MNIST.mp4	77.3 MB
9 -CNN for Fashion MNIST.vtt	12.0 KB
/7 - Recurrent Neural Networks, Time Series, and Sequence Data/
1 -Sequence Data.mp4	119.7 MB
1 -Sequence Data.vtt	26.4 KB
10 -GRU and LSTM (pt 2).mp4	52.9 MB
10 -GRU and LSTM (pt 2).vtt	13.4 KB
11 -A More Challenging Sequence.mp4	91.4 MB
11 -A More Challenging Sequence.vtt	9.5 KB
12 -RNN for Image Classification (Theory).mp4	33.8 MB
12 -RNN for Image Classification (Theory).vtt	5.4 KB
13 -RNN for Image Classification (Code).mp4	21.5 MB
13 -RNN for Image Classification (Code).vtt	2.9 KB
14 -Stock Return Predictions using LSTMs (pt 1).mp4	81.5 MB
14 -Stock Return Predictions using LSTMs (pt 1).vtt	14.3 KB
15 -Stock Return Predictions using LSTMs (pt 2).mp4	45.3 MB
15 -Stock Return Predictions using LSTMs (pt 2).vtt	6.1 KB
16 -Stock Return Predictions using LSTMs (pt 3).mp4	74.6 MB
16 -Stock Return Predictions using LSTMs (pt 3).vtt	12.9 KB
17 -Other Ways to Forecast.mp4	29.7 MB
17 -Other Ways to Forecast.vtt	6.5 KB
2 -Forecasting.mp4	50.7 MB
2 -Forecasting.vtt	12.4 KB
3 -Autoregressive Linear Model for Time Series Prediction.mp4	85.2 MB
3 -Autoregressive Linear Model for Time Series Prediction.vtt	13.1 KB
4 -Proof that the Linear Model Works.mp4	18.7 MB
4 -Proof that the Linear Model Works.vtt	4.1 KB
5 -Recurrent Neural Networks.mp4	97.1 MB
5 -Recurrent Neural Networks.vtt	22.9 KB
6 -RNN Code Preparation.mp4	57.9 MB
6 -RNN Code Preparation.vtt	15.9 KB
7 -RNN for Time Series Prediction.mp4	75.2 MB
7 -RNN for Time Series Prediction.vtt	8.9 KB
8 -Paying Attention to Shapes.mp4	59.1 MB
8 -Paying Attention to Shapes.vtt	9.9 KB
9 -GRU and LSTM (pt 1).mp4	83.7 MB
9 -GRU and LSTM (pt 1).vtt	20.4 KB
/8 - Natural Language Processing (NLP)/
1 -Embeddings.mp4	62.8 MB
1 -Embeddings.vtt	14.4 KB
10 -(Legacy) VIP Making Predictions with a Trained NLP Model.mp4	51.2 MB
10 -(Legacy) VIP Making Predictions with a Trained NLP Model.vtt	8.2 KB
11 -VIP Making Predictions with a Trained NLP Model (V2).mp4	26.7 MB
11 -VIP Making Predictions with a Trained NLP Model (V2).vtt	4.8 KB
2 -Neural Networks with Embeddings.mp4	16.4 MB
2 -Neural Networks with Embeddings.vtt	4.1 KB
3 -Text Preprocessing Concepts.mp4	54.8 MB
3 -Text Preprocessing Concepts.vtt	16.0 KB
4 -Beginner Blues - PyTorch NLP Version.mp4	67.2 MB
4 -Beginner Blues - PyTorch NLP Version.vtt	13.1 KB
4 -Why bad programmers always need the latest version.url	0.1 KB
5 -(Legacy) Text Preprocessing Code Preparation.mp4	46.5 MB
5 -(Legacy) Text Preprocessing Code Preparation.vtt	13.8 KB
6 -(Legacy) Text Preprocessing Code Example.mp4	50.1 MB
6 -(Legacy) Text Preprocessing Code Example.vtt	8.4 KB
7 -Text Classification with LSTMs (V2).mp4	122.9 MB
7 -Text Classification with LSTMs (V2).vtt	18.4 KB
8 -CNNs for Text.mp4	61.2 MB
8 -CNNs for Text.vtt	14.2 KB
9 -Text Classification with CNNs (V2).mp4	57.1 MB
9 -Text Classification with CNNs (V2).vtt	6.4 KB
/9 - Recommender Systems/
1 -Recommender Systems with Deep Learning Theory.mp4	67.9 MB
1 -Recommender Systems with Deep Learning Theory.vtt	12.2 KB
2 -Recommender Systems with Deep Learning Code Preparation.mp4	42.0 MB
2 -Recommender Systems with Deep Learning Code Preparation.vtt	11.4 KB
3 -Recommender Systems with Deep Learning Code (pt 1).mp4	72.9 MB
3 -Recommender Systems with Deep Learning Code (pt 1).vtt	9.8 KB
4 -Recommender Systems with Deep Learning Code (pt 2).mp4	80.5 MB
4 -Recommender Systems with Deep Learning Code (pt 2).vtt	15.6 KB
5 -VIP Making Predictions with a Trained Recommender Model.mp4	34.3 MB
5 -VIP Making Predictions with a Trained Recommender Model.vtt	5.4 KB
Total files 306