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[ CourseBoat com ] PluralSight - Deep Learning Literacy (Path)
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1. Literacy Essentials. Core Concepts Deep Learning (Pratheerth Padman, 2021)
1. Course Overview
1. Course Overview.mp4
1. Course Overview.vtt
2. Introduction to Deep Learning
1. Course Introduction and Module Overview.mp4
1. Course Introduction and Module Overview.vtt
2. What Is Deep Learning.mp4
2. What Is Deep Learning.vtt
3. Applications of Deep Learning in the Industry.mp4
3. Applications of Deep Learning in the Industry.vtt
4. Deep Learning Frameworks.mp4
4. Deep Learning Frameworks.vtt
5. Demo - Introduction to the Problem and Dataset.mp4
5. Demo - Introduction to the Problem and Dataset.vtt
6. Demo - Setting up Your Environment.mp4
6. Demo - Setting up Your Environment.vtt
7. Module Summary.mp4
7. Module Summary.vtt
3. The Inner Workings of Deep Learning
01. Module Overview.mp4
01. Module Overview.vtt
02. The Perceptron - From Biological to Artificial Neurons.mp4
02. The Perceptron - From Biological to Artificial Neurons.vtt
03. Activation Functions.mp4
03. Activation Functions.vtt
04. The Design and Working of a Neural Network.mp4
04. The Design and Working of a Neural Network.vtt
05. Gradient Descent.mp4
05. Gradient Descent.vtt
06. Demo - Basic Dataset Exploration.mp4
06. Demo - Basic Dataset Exploration.vtt
07. Demo - Preparing the Data - Part 1.mp4
07. Demo - Preparing the Data - Part 1.vtt
08. Demo - Preparing the Data - Part 2.mp4
08. Demo - Preparing the Data - Part 2.vtt
09. Demo - Building, Training, and Evaluating a Neural Network.mp4
09. Demo - Building, Training, and Evaluating a Neural Network.vtt
10. Module Summary.mp4
10. Module Summary.vtt
4. Types of Neural Networks and Their Uses
1. Module Overview.mp4
1. Module Overview.vtt
2. Convolutional Neural Networks.mp4
2. Convolutional Neural Networks.vtt
3. Recurrent Neural Networks.mp4
3. Recurrent Neural Networks.vtt
4. Long Short-term Memory Networks.mp4
4. Long Short-term Memory Networks.vtt
5. Generative Adversarial Networks.mp4
5. Generative Adversarial Networks.vtt
6. Autoencoders.mp4
6. Autoencoders.vtt
7. Module Summary and Course Feedback.mp4
7. Module Summary and Course Feedback.vtt
exercise.7z
playlist.m3u
~i.txt
2. Literacy Essentials. Core Concepts Neural Network (Abdul Rehman Yousaf, 2021)
1. Course Overview
1. Course Overview.mp4
1. Course Overview.vtt
2. Introducing Artificial Neural Networks
1. Module Overview.mp4
1. Module Overview.vtt
2. Inspiration from Biological Neurons.mp4
2. Inspiration from Biological Neurons.vtt
3. Brief History of Artificial Neural Networks.mp4
3. Brief History of Artificial Neural Networks.vtt
4. Introduction to Perceptron.mp4
4. Introduction to Perceptron.vtt
5. Summary.mp4
5. Summary.vtt
3. Understanding Neural Network’s Structure and Operations
1. Overview.mp4
1. Overview.vtt
2. Concepts of Bias and Weights.mp4
2. Concepts of Bias and Weights.vtt
3. Introducing Activation Functions.mp4
3. Introducing Activation Functions.vtt
4. Exploring Feed-forwarding Propagation.mp4
4. Exploring Feed-forwarding Propagation.vtt
5. Understand the Back-propagation.mp4
5. Understand the Back-propagation.vtt
6. Summary.mp4
6. Summary.vtt
4. Understanding Vectorized Neural Networks
1. Overview.mp4
1. Overview.vtt
2. What Is Vectorization in General.mp4
2. What Is Vectorization in General.vtt
3. Vectorization in the Context of Deep Learning.mp4
3. Vectorization in the Context of Deep Learning.vtt
4. Summary.mp4
4. Summary.vtt
exercise.7z
playlist.m3u
~i.txt
3. Literacy Essentials. Core Concepts Convolutional Neural Network (Alex Schultz, 2021)
02
introduction-slides.pdf
03
exploring-convolutional-neural-network-architecture-slides.pdf
04
next-steps-slides.pdf
1. Course Overview
1. Course Overview.mp4
1. Course Overview.vtt
2. Introduction
1. Introduction.mp4
1. Introduction.vtt
2. Course Outline.mp4
2. Course Outline.vtt
3. How Computers See Images.mp4
3. How Computers See Images.vtt
4. Solving Computer Vision Problems before Convolutional Neural Networks.mp4
4. Solving Computer Vision Problems before Convolutional Neural Networks.vtt
5. Common Convolutional Neural Network Use Cases.mp4
5. Common Convolutional Neural Network Use Cases.vtt
6. Summary.mp4
6. Summary.vtt
3. Exploring Convolutional Neural Network Architecture
1. Introduction.mp4
1. Introduction.vtt
2. Artificial Neural Networks.mp4
2. Artificial Neural Networks.vtt
3. Model Training.mp4
3. Model Training.vtt
4. Convolution Basics.mp4
4. Convolution Basics.vtt
5. Convolutional Layers.mp4
5. Convolutional Layers.vtt
6. Pooling Layer.mp4
6. Pooling Layer.vtt
7. CNN Structure.mp4
7. CNN Structure.vtt
8. Fine-tuning.mp4
8. Fine-tuning.vtt
9. Summary.mp4
9. Summary.vtt
4. Next Steps
1. Introduction.mp4
1. Introduction.vtt
2. Popular Convolutional Neural Networks.mp4
2. Popular Convolutional Neural Networks.vtt
3. Deep Learning Tools and Frameworks.mp4
3. Deep Learning Tools and Frameworks.vtt
4. Summary.mp4
4. Summary.vtt
playlist.m3u
~i.txt
4. Literacy Essentials. Core Concepts Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)
1. Course Overview
1. Course Overview.mp4
1. Course Overview.vtt
2. Understanding the Basics of Neural Networks
1. Overview.mp4
1. Overview.vtt
2. Introduction to Neural Networks.mp4
2. Introduction to Neural Networks.vtt
3. Exploring Important Concepts of NNs.mp4
3. Exploring Important Concepts of NNs.vtt
4. Explore Activation Functions in NNs.mp4
4. Explore Activation Functions in NNs.vtt
5. Explore Propagations in NNs.mp4
5. Explore Propagations in NNs.vtt
6. Summary.mp4
6. Summary.vtt
3. Introducing the Recurrent Neural Networks
1. Overview.mp4
1. Overview.vtt
2. What Is a Recurrent Neural Network and Why.mp4
2. What Is a Recurrent Neural Network and Why.vtt
3. How RNN Is Different from CNN.mp4
3. How RNN Is Different from CNN.vtt
4. Different Types and Architectures of RNN.mp4
4. Different Types and Architectures of RNN.vtt
5. Understand BackPropagation through Time in RNN.mp4
5. Understand BackPropagation through Time in RNN.vtt
6. Summary.mp4
6. Summary.vtt
4. Building a Recurrent Neural Network Using Tensorflow
1. Overview.mp4
1. Overview.vtt
2. Demo - Implement a Recurrent Neural Network Using TensorFlow.mp4
2. Demo - Implement a Recurrent Neural Network Using TensorFlow.vtt
3. Summary.mp4
3. Summary.vtt
5. Exploring the Merits of RNNs - Case Study
1. Overview.mp4
1. Overview.vtt
2. Introducing the Case Study.mp4
2. Introducing the Case Study.vtt
3. Support of Sequences in Recurrent Neural Networks.mp4
3. Support of Sequences in Recurrent Neural Networks.vtt
4. Taking Context into Account for Better Understanding.mp4
4. Taking Context into Account for Better Understanding.vtt
5. Summary.mp4
5. Summary.vtt
6. Understanding the Best Practices for Building RNNs
1. Overview.mp4
1. Overview.vtt
2. Best Practices for Improving the RNN Model Performance.mp4
2. Best Practices for Improving the RNN Model Performance.vtt
3. Considerations Regarding the Model Parameters.mp4
3. Considerations Regarding the Model Parameters.vtt
4. Summary.mp4
4. Summary.vtt
playlist.m3u
~i.txt
5. Literacy Essentials. Core Concepts Generative Adversarial Network (Jerry Kurata, 2022)
1. Course Overview
1. Course Overview.mp4
1. Course Overview.vtt
2. GAN Basics
1. GAN Basics.mp4
1. GAN Basics.vtt
2. Neural Network Basics.mp4
2. Neural Network Basics.vtt
3. Overview.mp4
3. Overview.vtt
3. How GANs Work
1. How GANs Work.mp4
1. How GANs Work.vtt
2. GAN Architecture.mp4
2. GAN Architecture.vtt
3. GAN Training.mp4
3. GAN Training.vtt
4. GAN Issues.mp4
4. GAN Issues.vtt
4. Using GANs to Solve Problems
1. Using GANs to Solve Problems.mp4
1. Using GANs to Solve Problems.vtt
2. Powerful Patterns with GANs.mp4
2. Powerful Patterns with GANs.vtt
3. Use GANs to Generate Training Data.mp4
3. Use GANs to Generate Training Data.vtt
4. Summary.mp4
4. Summary.vtt
5. Exploring Example GANs
1. Exploring Example GANs.mp4
1. Exploring Example GANs.vtt
2. Course Summary.mp4
2. Course Summary.vtt
exercise.7z
playlist.m3u
~i.txt
6. Literacy Essentials. Core Concepts Recommender Systems (Biswanath Halder, 2022)
1. Course Overview
1. Course Overview.mp4
1. Course Overview.vtt
2. Introduction to Recommendation Systems
1. Overview.mp4
1. Overview.vtt
2. Examples of Recommender Systems.mp4
2. Examples of Recommender Systems.vtt
3. Definition of Recommender System.mp4
3. Definition of Recommender System.vtt
4. Benefits of Recommender Systems.mp4
4. Benefits of Recommender Systems.vtt
5. Types of Recommender Systems.mp4
5. Types of Recommender Systems.vtt
6. Evaluation Criteria of Recommender Systems.mp4
6. Evaluation Criteria of Recommender Systems.vtt
7. Summary.mp4
7. Summary.vtt
3. Collaborative-filtering Based Recommendation Systems
1. Overview.mp4
1. Overview.vtt
2. Introduction to Collaborative Filtering.mp4
2. Introduction to Collaborative Filtering.vtt
3. How to Quantify Similarity.mp4
3. How to Quantify Similarity.vtt
4. Collaborative Filtering in the Neighborhood.mp4
4. Collaborative Filtering in the Neighborhood.vtt
5. Pros and Cons of Collaborative Filtering.mp4
5. Pros and Cons of Collaborative Filtering.vtt
6. Summary.mp4
6. Summary.vtt
4. Build a Product Recommendation System for Globomantics Using Python
1. Overview.mp4
1. Overview.vtt
2. Data Exploration.mp4
2. Data Exploration.vtt
3. Data Cleaning.mp4
3. Data Cleaning.vtt
4. Generate Non-personalized Recommendations.mp4
4. Generate Non-personalized Recommendations.vtt
5. Create User-item Interaction Matrix.mp4
5. Create User-item Interaction Matrix.vtt
6. Generate Recommendations Using User Based Collab.mp4
6. Generate Recommendations Using User Based Collab.vtt
7. Generate Recommendations Using Item Based Collab.mp4
7. Generate Recommendations Using Item Based Collab.vtt
8. Summary.mp4
8. Summary.vtt
5. Other Approaches to Generate Recommendations
1. Overview.mp4
1. Overview.vtt
2. Content-based Recommendation Systems.mp4
2. Content-based Recommendation Systems.vtt
3. Context-aware Recommendation Systems.mp4
3. Context-aware Recommendation Systems.vtt
4. Model-based Recommendation Systems.mp4
4. Model-based Recommendation Systems.vtt
5. Hybrid Recommendation Systems.mp4
5. Hybrid Recommendation Systems.vtt
6. Summary.mp4
6. Summary.vtt
exercise.7z
playlist.m3u
~i.txt
7. Literacy Essentials. Core Concepts Data Normalization (Ifedayo Bamikole, 2022)
1. Course Overview
1. Course Overview.mp4
1. Course Overview.vtt
2. Evaluate Normalization Techniques for Deep Learning
1. Introduction.mp4
1. Introduction.vtt
2. What Is Deep Learning.mp4
2. What Is Deep Learning.vtt
3. Deep Learning Use Cases.mp4
3. Deep Learning Use Cases.vtt
4. What Are Neural Networks.mp4
4. What Are Neural Networks.vtt
5. Challenges in Designing a Deep Learning Solution.mp4
5. Challenges in Designing a Deep Learning Solution.vtt
6. What Is Data Normalization.mp4
6. What Is Data Normalization.vtt
7. Normalization Demo.mp4
7. Normalization Demo.vtt
8. Conclusion.mp4
8. Conclusion.vtt
3. Understand Types of Normalization
1. Introduction.mp4
1. Introduction.vtt
2. Batch Normalization.mp4
2. Batch Normalization.vtt
3. Convolutional Neural Network.mp4
3. Convolutional Neural Network.vtt
4. Layer Normalization.mp4
4. Layer Normalization.vtt
5. Instance Normalization.mp4
5. Instance Normalization.vtt
6. Group Normalization.mp4
6. Group Normalization.vtt
7. Conclusion.mp4
7. Conclusion.vtt
4. Case Study on Appropriate Normalization Technique
1. Introduction.mp4
1. Introduction.vtt
2. Quick Overview.mp4
2. Quick Overview.vtt
3. Demo - Create A Deep Learning Model With Normalization.mp4
3. Demo - Create A Deep Learning Model With Normalization.vtt
4. Conclusion.mp4
4. Conclusion.vtt
exercise.7z
playlist.m3u
~i.txt
Bonus Resources.txt
scr.png
~i.txt
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