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Download [LinkedIn Learning] Getting Started with AI and Machine Learning - Complete 7 Courses

LinkedIn Learning Getting Started with AI and Machine Learning Complete Courses

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[LinkedIn Learning] Getting Started with AI and Machine Learning - Complete 7 Courses

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1.9 GB

Total Files

408

Last Seen

2025-03-08 00:20

Hash

AD3F47E9AA6BF9084D2D7E77062D9A0DD0A4A4A7

/

$10 ChatGPT for 1 Year & More.txt

0.3 KB

/0 - Introduction/

2. What you should know.srt

0.9 KB

1. Neural networks 101 Your path to AI brilliance.srt

1.3 KB

3. How to use the challenge exercise files.srt

2.1 KB

2. What you should know.mp4

1.7 MB

3. How to use the challenge exercise files.mp4

3.9 MB

1. Neural networks 101 Your path to AI brilliance.mp4

4.6 MB

/.../2 - Reinforcement Learning Algorithms/

3. Other RL algorithms.srt

0.9 KB

2. Temporal difference methods.srt

1.8 KB

1. Monte Carlo method.srt

4.9 KB

2. Temporal difference methods.mp4

2.4 MB

3. Other RL algorithms.mp4

3.3 MB

1. Monte Carlo method.mp4

12.8 MB

/7 - Conclusion/

1. Extending your deep learning education.srt

1.1 KB

1. Extending your deep learning education.mp4

1.6 MB

/Reinforcement Learning Foundations/

description.html

1.1 KB

/Hands-On PyTorch Machine Learning/

description.html

1.1 KB

Ex_Files_Hands_On_PyTorch_ML.zip

7.2 MB

/.../5 - Best Practices for Optimizing a Neural Network/

5. Challenge Manually tune hyperparameters.srt

1.1 KB

6. Solution Manually tune hyperparameters.srt

2.5 KB

2. Hyperparameters and neural networks.srt

4.6 KB

3. How do you improve model performance.srt

5.8 KB

1. Overfitting and underfitting Two common ANN problems.srt

7.5 KB

4. Regularization techniques to improve overfitting models.srt

11.6 KB

5. Challenge Manually tune hyperparameters.mp4

1.2 MB

2. Hyperparameters and neural networks.mp4

6.3 MB

6. Solution Manually tune hyperparameters.mp4

6.4 MB

3. How do you improve model performance.mp4

6.5 MB

1. Overfitting and underfitting Two common ANN problems.mp4

7.2 MB

4. Regularization techniques to improve overfitting models.mp4

12.4 MB

/Machine Learning Foundations Linear Algebra/

description.html

1.1 KB

Ex_Files_ML_Foundations_Linear_Algebra.zip

34.1 KB

/Building Computer Vision Applications with Python/

description.html

1.2 KB

Ex_Files_Computer_Vision_Deep_Dive_in_Python.zip

152.8 MB

/8 - Conclusion/

1. Next steps.srt

1.2 KB

1. Next steps.mp4

2.6 MB

/.../4 - Build a Simple Neural Network Using Keras/

6. Challenge Build a neural network.srt

1.2 KB

4. Data preprocessing.srt

2.9 KB

3. Data checks and data preparation.srt

3.8 KB

7. Solution Build a neural network.srt

5.6 KB

1. The Keras Sequential model.srt

6.0 KB

2. Use case and determine evaluation metric.srt

7.4 KB

5. Train the neural network using Keras.srt

8.6 KB

6. Challenge Build a neural network.mp4

1.3 MB

4. Data preprocessing.mp4

3.8 MB

3. Data checks and data preparation.mp4

4.9 MB

1. The Keras Sequential model.mp4

6.8 MB

2. Use case and determine evaluation metric.mp4

10.3 MB

5. Train the neural network using Keras.mp4

10.8 MB

7. Solution Build a neural network.mp4

11.3 MB

/8 - Conclusion/

1. Next steps.srt

1.2 KB

1. Next steps.mp4

1.9 MB

/Deep Learning Getting Started/

description.html

1.2 KB

Ex_Files_Deep_Learning_Getting_Started.zip

105.4 KB

/.../6 - Deep Learning Exercise/

3. Building the RCA model.srt

1.2 KB

4. Predicting root causes with deep learning.srt

1.5 KB

2. Preprocessing RCA data.srt

1.5 KB

1. Exercise problem statement.srt

3.9 KB

4. Predicting root causes with deep learning.mp4

2.8 MB

3. Building the RCA model.mp4

3.8 MB

2. Preprocessing RCA data.mp4

4.2 MB

1. Exercise problem statement.mp4

6.1 MB

/Artificial Intelligence Foundations Neural Networks/

description.html

1.2 KB

/Artificial Intelligence Foundations Thinking Machines/

description.html

1.3 KB

/0 - Introduction/

1. Explore the capabilities of PyTorch.srt

1.4 KB

1. Explore the capabilities of PyTorch.mp4

2.7 MB

/5 - Image Scaling/

5. Challenge Resize a picture.srt

1.4 KB

6. Solution Resize a picture.srt

1.8 KB

3. Image upscaling methods.srt

2.8 KB

1. Image downscaling methods.srt

3.3 KB

2. Downscaling example.srt

4.7 KB

4. Upscaling example.srt

5.1 KB

5. Challenge Resize a picture.mp4

3.1 MB

3. Image upscaling methods.mp4

3.7 MB

1. Image downscaling methods.mp4

4.4 MB

6. Solution Resize a picture.mp4

6.4 MB

2. Downscaling example.mp4

11.9 MB

4. Upscaling example.mp4

12.2 MB

/.../3 - From Color to Black and White/

5. Challenge Removing color.srt

1.4 KB

6. Solution Removing color.srt

1.5 KB

2. Weighted grayscale.srt

2.0 KB

3. Converting grayscale to black and white.srt

4.2 KB

1. Average grayscale.srt

5.2 KB

4. Adaptive thresholding.srt

7.3 KB

5. Challenge Removing color.mp4

3.0 MB

6. Solution Removing color.mp4

4.4 MB

2. Weighted grayscale.mp4

6.5 MB

3. Converting grayscale to black and white.mp4

11.0 MB

1. Average grayscale.mp4

11.4 MB

4. Adaptive thresholding.mp4

22.0 MB

/.../3 - Monte Carlo Method/

5. Monte Carlo control.srt

1.4 KB

1. The setting.srt

2.2 KB

3. Monte Carlo prediction.srt

2.7 KB

4. First visit and every visit MC prediction.srt

2.8 KB

2. Exploration and exploitation.srt

3.6 KB

6. Additional modifications.srt

4.3 KB

5. Monte Carlo control.mp4

1.5 MB

3. Monte Carlo prediction.mp4

2.5 MB

1. The setting.mp4

3.4 MB

6. Additional modifications.mp4

4.8 MB

4. First visit and every visit MC prediction.mp4

7.2 MB

2. Exploration and exploitation.mp4

8.1 MB

/0 - Introduction/

3. Using the exercise files.srt

1.4 KB

1. Computer vision under the hood.srt

2.2 KB

2. What you should know.srt

2.2 KB

3. Using the exercise files.mp4

1.9 MB

2. What you should know.mp4

2.9 MB

1. Computer vision under the hood.mp4

7.7 MB

/0 - Introduction/

1. Reinforcement learning in a nutshell.srt

1.5 KB

1. Reinforcement learning in a nutshell.mp4

3.8 MB

/0 - Introduction/

1. Getting started with deep learning.srt

1.5 KB

3. Setting up the environment.srt

3.7 KB

2. Prerequisites for the course.srt

4.2 KB

1. Getting started with deep learning.mp4

4.2 MB

2. Prerequisites for the course.mp4

5.1 MB

3. Setting up the environment.mp4

6.3 MB

/0 - Introduction/

1. Introduction.srt

1.6 KB

2. What you should know.srt

1.7 KB

2. What you should know.mp4

5.6 MB

1. Introduction.mp4

9.0 MB

/.../1 - Setting Up Your Environment/

1. Installing Anaconda and OpenCV.srt

1.7 KB

2. Testing your environment.srt

5.6 KB

1. Installing Anaconda and OpenCV.mp4

2.0 MB

2. Testing your environment.mp4

11.1 MB

/.../5 - Modified Forms of Reinforcement/

2. Multi-agent reinforcement learning.srt

1.7 KB

3. Inverse reinforcement learning.srt

1.8 KB

1. Deep reinforcement learning.srt

2.3 KB

2. Multi-agent reinforcement learning.mp4

1.9 MB

3. Inverse reinforcement learning.mp4

2.3 MB

1. Deep reinforcement learning.mp4

4.5 MB

/4 - Filters/

7. Solution Convolution filters.srt

1.7 KB

6. Challenge Convolution filters.srt

2.0 KB

4. Gaussian filters.srt

3.0 KB

2. Average filters.srt

4.3 KB

5. Edge detection filters.srt

6.1 KB

1. Convolution filters.srt

6.5 KB

3. Median filters.srt

7.0 KB

6. Challenge Convolution filters.mp4

5.0 MB

7. Solution Convolution filters.mp4

6.5 MB

4. Gaussian filters.mp4

8.6 MB

1. Convolution filters.mp4

8.9 MB

2. Average filters.mp4

11.9 MB

5. Edge detection filters.mp4

14.9 MB

3. Median filters.mp4

26.6 MB

/.../6 - Fun with Cuts/

4. Challenge Stitch two pictures together.srt

1.8 KB

5. Solution Stitch two pictures together.srt

1.9 KB

3. Cuts in panoramic photography.srt

4.9 KB

1. Image cuts.srt

5.9 KB

2. Stitching two images together.srt

10.1 KB

4. Challenge Stitch two pictures together.mp4

3.8 MB

5. Solution Stitch two pictures together.mp4

6.7 MB

3. Cuts in panoramic photography.mp4

13.1 MB

1. Image cuts.mp4

14.4 MB

2. Stitching two images together.mp4

46.3 MB

/8 - Conclusion/

1. Next steps.srt

1.8 KB

1. Next steps.mp4

4.5 MB

/.../4 - Temporal Difference Methods/

1. The setting.srt

1.9 KB

4. Expected SARSA.srt

2.6 KB

3. SARSAMAX (Q-learning).srt

3.3 KB

2. SARSA.srt

7.0 KB

1. The setting.mp4

5.4 MB

4. Expected SARSA.mp4

7.4 MB

3. SARSAMAX (Q-learning).mp4

9.6 MB

2. SARSA.mp4

15.9 MB

/6 - Conclusion/

1. Continuing your PyTorch learning process.srt

1.9 KB

1. Continuing your PyTorch learning process.mp4

1.8 MB

/3 - Torchvision/

2. Torchvision for video and image understanding.srt

1.9 KB

1. Torchvision introduction.srt

12.3 KB

2. Torchvision for video and image understanding.mp4

4.7 MB

1. Torchvision introduction.mp4

14.4 MB

/.../4 - Deep Learning Example 1/

5. Saving and loading models.srt

2.0 KB

1. The Iris classification problem.srt

2.3 KB

6. Predictions with deep learning models.srt

2.5 KB

3. Creating a deep learning model.srt

4.1 KB

2. Input preprocessing.srt

4.3 KB

4. Training and evaluation.srt

4.4 KB

5. Saving and loading models.mp4

3.2 MB

6. Predictions with deep learning models.mp4

4.8 MB

1. The Iris classification problem.mp4

4.9 MB

3. Creating a deep learning model.mp4

8.5 MB

2. Input preprocessing.mp4

9.9 MB

4. Training and evaluation.mp4

9.9 MB

/7 - Morphological Modifications/

5. Solution Help a robot.srt

2.0 KB

3. Open and close.srt

2.8 KB

4. Challenge Help a robot.srt

3.5 KB

2. Erosion and dilation.srt

5.4 KB

1. Why modify objects.srt

7.6 KB

3. Open and close.mp4

7.5 MB

5. Solution Help a robot.mp4

8.3 MB

4. Challenge Help a robot.mp4

9.5 MB

2. Erosion and dilation.mp4

12.0 MB

1. Why modify objects.mp4

14.5 MB

/.../5 - Deep Learning Example 2/

3. Building a spam model.srt

2.0 KB

4. Predictions for text.srt

2.3 KB

1. Spam classification problem.srt

2.9 KB

2. Creating text representations.srt

3.1 KB

1. Spam classification problem.mp4

3.9 MB

4. Predictions for text.mp4

4.3 MB

3. Building a spam model.mp4

5.5 MB

2. Creating text representations.mp4

7.5 MB

/.../3 - Training a Neural Network/

2. Forward propagation.srt

2.2 KB

5. Gradient descent.srt

2.4 KB

7. Validation and testing.srt

2.7 KB

8. An ANN model.srt

3.1 KB

10. Using available open-source models.srt

3.8 KB

3. Measuring accuracy and error.srt

3.8 KB

4. Back propagation.srt

3.9 KB

6. Batches and epochs.srt

4.0 KB

9. Reusing existing network architectures.srt

4.0 KB

1. Setup and initialization.srt

4.9 KB

2. Forward propagation.mp4

2.9 MB

5. Gradient descent.mp4

3.2 MB

7. Validation and testing.mp4

3.4 MB

8. An ANN model.mp4

3.7 MB

9. Reusing existing network architectures.mp4

4.4 MB

10. Using available open-source models.mp4

4.5 MB

3. Measuring accuracy and error.mp4

5.0 MB

4. Back propagation.mp4

5.0 MB

6. Batches and epochs.mp4

5.0 MB

1. Setup and initialization.mp4

6.0 MB

/.../1 - What Are Neural Networks/

3. Artificial neural networks.srt

2.5 KB

2. Biological neural networks.srt

3.6 KB

4. Single-layer perceptron.srt

5.4 KB

1. Machine learning and neural networks.srt

6.2 KB

3. Artificial neural networks.mp4

3.0 MB

2. Biological neural networks.mp4

5.3 MB

4. Single-layer perceptron.mp4

6.7 MB

1. Machine learning and neural networks.mp4

9.2 MB

/.../1 - Introduction to Deep Learning/

4. The perceptron.srt

2.7 KB

1. What is deep learning.srt

2.8 KB

6. Training an ANN.srt

4.1 KB

2. Linear regression.srt

4.3 KB

5. Artificial neural networks.srt

4.4 KB

3. An analogy for deep learning.srt

4.5 KB

4. The perceptron.mp4

2.7 MB

1. What is deep learning.mp4

2.8 MB

3. An analogy for deep learning.mp4

4.7 MB

6. Training an ANN.mp4

5.4 MB

2. Linear regression.mp4

5.8 MB

5. Artificial neural networks.mp4

6.1 MB

/6 - Conclusion/

1. Next steps.srt

2.7 KB

1. Next steps.mp4

2.7 MB

/.../2 - Neural Network Architecture/

5. The output layer.srt

2.8 KB

2. Hidden layers.srt

2.9 KB

4. Activation functions.srt

3.6 KB

3. Weights and biases.srt

4.3 KB

1. The input layer.srt

4.7 KB

5. The output layer.mp4

3.6 MB

4. Activation functions.mp4

4.1 MB

2. Hidden layers.mp4

4.9 MB

3. Weights and biases.mp4

5.9 MB

1. The input layer.mp4

6.2 MB

/6 - Conclusion/

1. Your reinforcement learning journey.srt

2.9 KB

1. Your reinforcement learning journey.mp4

6.5 MB

/.../2 - The Basics of Image Processing/

5. Rotations and flips.srt

2.9 KB

6. Challenge Manipulate some pictures.srt

3.7 KB

7. Solution Manipulate some pictures.srt

3.8 KB

2. Color encoding.srt

4.3 KB

4. Resolution.srt

4.6 KB

1. Image representation.srt

5.9 KB

3. Image file management.srt

8.6 KB

5. Rotations and flips.mp4

6.4 MB

6. Challenge Manipulate some pictures.mp4

7.6 MB

2. Color encoding.mp4

8.3 MB

4. Resolution.mp4

9.2 MB

7. Solution Manipulate some pictures.mp4

10.0 MB

1. Image representation.mp4

12.7 MB

3. Image file management.mp4

20.1 MB

/2 - PyTorch Basics/

5. Advanced PyTorch autograd.srt

3.2 KB

2. Understand PyTorch basic operations.srt

3.9 KB

4. Understand PyTorch autograd.srt

4.2 KB

3. Understand PyTorch NumPy Bridge.srt

5.0 KB

1. Understand PyTorch tensors.srt

5.1 KB

5. Advanced PyTorch autograd.mp4

5.3 MB

4. Understand PyTorch autograd.mp4

5.7 MB

1. Understand PyTorch tensors.mp4

7.4 MB

2. Understand PyTorch basic operations.mp4

7.9 MB

3. Understand PyTorch NumPy Bridge.mp4

8.5 MB

/.../6 - Matrices from Orthogonality to Gram–Schmidt Process/

3. Orthogonal matrix.srt

3.3 KB

1. Matrices changing basis.srt

3.3 KB

2. Transforming to the new basis.srt

3.7 KB

4. Gram–Schmidt process.srt

4.1 KB

3. Orthogonal matrix.mp4

6.9 MB

1. Matrices changing basis.mp4

7.7 MB

4. Gram–Schmidt process.mp4

11.6 MB

2. Transforming to the new basis.mp4

15.1 MB

/0 - Introduction/

1. Welcome.srt

3.4 KB

1. Welcome.mp4

7.4 MB

/.../1 - Introduction to Linear Algebra/

1. Defining linear algebra.srt

3.5 KB

2. Applications of linear algebra in ML.srt

7.8 KB

1. Defining linear algebra.mp4

11.7 MB

2. Applications of linear algebra in ML.mp4

23.9 MB

/.../1 - Getting Started with Reinforcement Learning/

4. A basic RL solution.srt

3.6 KB

1. Terms in reinforcement learning.srt

3.8 KB

2. A basic RL problem.srt

6.8 KB

3. Markov decision process.srt

7.1 KB

4. A basic RL solution.mp4

9.0 MB

1. Terms in reinforcement learning.mp4

10.7 MB

2. A basic RL problem.mp4

15.8 MB

3. Markov decision process.mp4

18.2 MB

/1 - Preparation/

3. PyTorch use case description.srt

3.7 KB

4. PyTorch data exploration.srt

5.6 KB

2. PyTorch environment setup.srt

5.6 KB

1. PyTorch overview.srt

5.9 KB

3. PyTorch use case description.mp4

3.8 MB

1. PyTorch overview.mp4

8.1 MB

4. PyTorch data exploration.mp4

12.7 MB

2. PyTorch environment setup.mp4

13.7 MB

/.../4 - Introduction to Matrices/

1. Matrices introduction.srt

3.9 KB

2. Types of matrices.srt

4.4 KB

4. Composition or combination of matrix transformations.srt

4.4 KB

3. Types of matrix transformation.srt

4.4 KB

1. Matrices introduction.mp4

8.8 MB

3. Types of matrix transformation.mp4

9.3 MB

2. Types of matrices.mp4

10.1 MB

4. Composition or combination of matrix transformations.mp4

12.3 MB

/5 - Gaussian Elimination/

3. Inverse and determinant.srt

4.0 KB

2. Gaussian elimination and finding the inverse matrix.srt

4.5 KB

1. Solving linear equations using Gaussian elimination.srt

6.2 KB

3. Inverse and determinant.mp4

8.8 MB

2. Gaussian elimination and finding the inverse matrix.mp4

10.2 MB

1. Solving linear equations using Gaussian elimination.mp4

17.9 MB

/.../7 - Eigenvalues and Eigenvectors/

1. Introduction to eigenvalues and eigenvectors.srt

4.1 KB

2. Calculating eigenvalues and eigenvectors.srt

4.5 KB

3. Changing to the eigenbasis.srt

5.8 KB

4. Google PageRank algorithm.srt

6.1 KB

1. Introduction to eigenvalues and eigenvectors.mp4

10.9 MB

2. Calculating eigenvalues and eigenvectors.mp4

12.1 MB

4. Google PageRank algorithm.mp4

13.0 MB

3. Changing to the eigenbasis.mp4

13.8 MB

/.../3 - Vector Projections and Basis/

4. Basis, linear independence, and span.srt

4.1 KB

1. Dot product of vectors.srt

4.5 KB

2. Scalar and vector projection.srt

5.0 KB

3. Changing basis of vectors.srt

6.6 KB

4. Basis, linear independence, and span.mp4

12.6 MB

1. Dot product of vectors.mp4

13.0 MB

2. Scalar and vector projection.mp4

14.4 MB

3. Changing basis of vectors.mp4

18.0 MB

/.../2 - Key Components in Neural Network Architecture/

2. Layers Input, hidden, and output.srt

4.1 KB

3. Transfer and activation functions.srt

5.1 KB

1. Multilayer perceptron.srt

6.0 KB

4. How neural networks learn.srt

7.0 KB

2. Layers Input, hidden, and output.mp4

4.8 MB

3. Transfer and activation functions.mp4

6.0 MB

1. Multilayer perceptron.mp4

7.1 MB

4. How neural networks learn.mp4

9.3 MB

/2 - Vectors Basics/

3. Coordinate system.srt

4.3 KB

2. Vector arithmetic.srt

5.6 KB

1. Introduction to vectors.srt

7.0 KB

3. Coordinate system.mp4

10.3 MB

2. Vector arithmetic.mp4

13.0 MB

1. Introduction to vectors.mp4

31.4 MB

/4 - Torchaudio/

1. Torchaudio introduction.srt

4.9 KB

2. Torchaudio for audio understanding.srt

5.5 KB

1. Torchaudio introduction.mp4

6.9 MB

2. Torchaudio for audio understanding.mp4

13.9 MB

/5 - Torchtext/

1. Torchtext introduction.srt

5.1 KB

2. Torchtext for translation.srt

5.6 KB

1. Torchtext introduction.mp4

8.3 MB

2. Torchtext for translation.mp4

15.0 MB

/.../6 - What Has Changed/

3. Self-supervised learning.srt

5.3 KB

2. Foundation models.srt

5.7 KB

1. Generative AI.srt

5.9 KB

3. Self-supervised learning.mp4

12.0 MB

1. Generative AI.mp4

12.2 MB

2. Foundation models.mp4

13.2 MB

/.../3 - Other Types of Neural Networks/

3. Transformer architecture.srt

5.7 KB

2. Recurrent neural networks (RNN).srt

10.1 KB

1. Convolutional neural networks (CNN).srt

12.5 KB

3. Transformer architecture.mp4

8.2 MB

2. Recurrent neural networks (RNN).mp4

13.4 MB

1. Convolutional neural networks (CNN).mp4

16.3 MB

/.../4 - Common AI Programs/

3. The Internet of Things.srt

7.1 KB

1. Robotics.srt

8.3 KB

2. Natural language processing.srt

8.4 KB

3. The Internet of Things.mp4

12.3 MB

1. Robotics.mp4

14.9 MB

2. Natural language processing.mp4

15.2 MB

/.../3 - Finding the Right Approach/

4. Backpropagation.srt

7.8 KB

2. Data vs. reasoning.srt

8.3 KB

3. Unsupervised learning.srt

8.3 KB

1. Match patterns.srt

8.3 KB

5. Regression.srt

9.1 KB

2. Data vs. reasoning.mp4

11.9 MB

4. Backpropagation.mp4

13.6 MB

5. Regression.mp4

14.2 MB

3. Unsupervised learning.mp4

14.3 MB

1. Match patterns.mp4

16.3 MB

/.../5 - Mixing with Other Technologies/

1. Big data.srt

7.8 KB

2. Data science.srt

8.2 KB

1. Big data.mp4

13.3 MB

2. Data science.mp4

13.7 MB

/.../2 - The Rise of Machine Learning/

2. Artificial neural networks.srt

8.0 KB

1. Machine learning.srt

8.5 KB

3. Perceptrons.srt

8.7 KB

2. Artificial neural networks.mp4

13.7 MB

1. Machine learning.mp4

14.4 MB

3. Perceptrons.mp4

14.8 MB

/.../1 - What Is Artificial Intelligence/

2. The history of AI.srt

8.1 KB

3. Strong vs. weak AI.srt

8.5 KB

4. Plan AI.srt

8.6 KB

1. Define general intelligence.srt

8.6 KB

2. The history of AI.mp4

10.9 MB

1. Define general intelligence.mp4

12.5 MB

3. Strong vs. weak AI.mp4

13.6 MB

4. Plan AI.mp4

14.6 MB

/7 - Avoiding Pitfalls/

1. Pitfalls.srt

8.4 KB

1. Pitfalls.mp4

12.9 MB

 

Total files 408


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