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Path Deep Learning Literacy (2022)

Category: Tutorials


Path  Deep Learning Literacy (2022)
728.16 MB | 00:08:14 | mp4 | 1280X720 | 16:9
Genre:eLearning |Language:English



Files Included :
1 Course Overview.mp4 (3.39 MB)
1 Course Introduction and Module Overview.mp4 (5.27 MB)
2 What Is Deep Learning.mp4 (5.99 MB)
3 Applications of Deep Learning in the Industry.mp4 (11.43 MB)
4 Deep Learning Frameworks.mp4 (4.48 MB)
5 Demo - Introduction to the Problem and Dataset.mp4 (5.44 MB)
6 Demo - Setting up Your Environment.mp4 (6.05 MB)
7 Module Summary.mp4 (1.42 MB)
01 Module Overview.mp4 (1.34 MB)
02 The Perceptron - From Biological to Artificial Neurons.mp4 (4.91 MB)
03 Activation Functions.mp4 (7.14 MB)
04 The Design and Working of a Neural Network.mp4 (10.15 MB)
05 Gradient Descent.mp4 (5.99 MB)
06 Demo - Basic Dataset Exploration.mp4 (14.34 MB)
07 Demo - Preparing the Data - Part 1.mp4 (14.73 MB)
08 Demo - Preparing the Data - Part 2.mp4 (12.92 MB)
09 Demo - Building, Training, and Evaluating a Neural Network.mp4 (19.11 MB)
10 Module Summary.mp4 (1.25 MB)
1 Module Overview.mp4 (1.87 MB)
2 Convolutional Neural Networks.mp4 (2.99 MB)
3 Recurrent Neural Networks.mp4 (3.35 MB)
4 Long Short-term Memory Networks.mp4 (3.42 MB)
5 Generative Adversarial Networks.mp4 (4.01 MB)
6 Autoencoders.mp4 (3.72 MB)
7 Module Summary and Course Feedback.mp4 (1.82 MB)
1 Course Overview.mp4 (2.43 MB)
1 Module Overview.mp4 (4.86 MB)
2 Inspiration from Biological Neurons.mp4 (10.31 MB)
3 Brief History of Artificial Neural Networks.mp4 (2.81 MB)
4 Introduction to Perceptron.mp4 (2.88 MB)
5 Summary.mp4 (1.22 MB)
1 Overview.mp4 (1.6 MB)
2 Concepts of Bias and Weights.mp4 (8.81 MB)
3 Introducing Activation Functions.mp4 (11.05 MB)
4 Exploring Feed-forwarding Propagation.mp4 (8.68 MB)
5 Understand the Back-propagation.mp4 (11.3 MB)
6 Summary.mp4 (3.14 MB)
1 Overview.mp4 (717.58 KB)
2 What Is Vectorization in General.mp4 (6.24 MB)
3 Vectorization in the Context of Deep Learning.mp4 (9.08 MB)
4 Summary.mp4 (1.14 MB)
1 Course Overview.mp4 (2.81 MB)
1 Introduction.mp4 (3.04 MB)
2 Course Outline.mp4 (2.79 MB)
3 How Computers See Images.mp4 (11.42 MB)
4 Solving Computer Vision Problems before Convolutional Neural Networks.mp4 (4.52 MB)
5 Common Convolutional Neural Network Use Cases.mp4 (3.86 MB)
6 Summary.mp4 (2.03 MB)
1 Introduction.mp4 (2.14 MB)
2 Artificial Neural Networks.mp4 (12.74 MB)
3 Model Training.mp4 (10.2 MB)
4 Convolution Basics.mp4 (6.47 MB)
5 Convolutional Layers.mp4 (17.68 MB)
6 Pooling Layer.mp4 (2.55 MB)
7 CNN Structure.mp4 (3.14 MB)
8 Fine-tuning.mp4 (4.59 MB)
9 Summary.mp4 (2.53 MB)
1 Introduction.mp4 (805.19 KB)
2 Popular Convolutional Neural Networks.mp4 (7.53 MB)
3 Deep Learning Tools and Frameworks.mp4 (15.71 MB)
4 Summary.mp4 (1006.52 KB)
exercise.zip (5.06 MB)
1 Course Overview.mp4 (3.34 MB)
1 Overview.mp4 (2.06 MB)
2 Introduction to Neural Networks.mp4 (2.79 MB)
3 Exploring Important Concepts of NNs.mp4 (8.22 MB)
4 Explore Activation Functions in NNs.mp4 (14.64 MB)
5 Explore Propagations in NNs.mp4 (6.44 MB)
6 Summary.mp4 (1.05 MB)
1 Overview.mp4 (1.51 MB)
2 What Is a Recurrent Neural Network and Why.mp4 (7.83 MB)
3 How RNN Is Different from CNN.mp4 (4.52 MB)
4 Different Types and Architectures of RNN.mp4 (16.65 MB)
5 Understand BackPropagation through Time in RNN.mp4 (4.35 MB)
6 Summary.mp4 (1.36 MB)
1 Overview.mp4 (590.17 KB)
3 Summary.mp4 (483.7 KB)
1 Overview.mp4 (570.47 KB)
2 Introducing the Case Study.mp4 (2.96 MB)
3 Support of Sequences in Recurrent Neural Networks.mp4 (3.99 MB)
5 Summary.mp4 (1.18 MB)
1 Overview.mp4 (646.37 KB)
4 Summary.mp4 (1.01 MB)
1 Course Overview.mp4 (2.53 MB)
1 GAN Basics.mp4 (3.06 MB)
2 Neural Network Basics.mp4 (8.15 MB)
3 Overview.mp4 (1.78 MB)
1 How GANs Work.mp4 (6.36 MB)
2 GAN Architecture.mp4 (3.73 MB)
3 GAN Training.mp4 (7.46 MB)
4 GAN Issues.mp4 (2.75 MB)
1 Using GANs to Solve Problems.mp4 (976.46 KB)
2 Powerful Patterns with GANs.mp4 (5.28 MB)
3 Use GANs to Generate Training Data.mp4 (7.64 MB)
4 Summary.mp4 (619.29 KB)
1 Exploring Example GANs.mp4 (6.65 MB)
2 Course Summary.mp4 (2.61 MB)
1 Course Overview.mp4 (2.7 MB)
1 Overview.mp4 (1.13 MB)
2 Examples of Recommender Systems.mp4 (1.9 MB)
3 Definition of Recommender System.mp4 (3.84 MB)
4 Benefits of Recommender Systems.mp4 (1.58 MB)
5 Types of Recommender Systems.mp4 (2.54 MB)
6 Evaluation Criteria of Recommender Systems.mp4 (3.57 MB)
7 Summary.mp4 (1.17 MB)
1 Overview.mp4 (1.15 MB)
2 Introduction to Collaborative Filtering.mp4 (5.3 MB)
3 How to Quantify Similarity.mp4 (8.71 MB)
4 Collaborative Filtering in the Neighborhood.mp4 (7.21 MB)
5 Pros and Cons of Collaborative Filtering.mp4 (3.82 MB)
6 Summary.mp4 (1.28 MB)
1 Overview.mp4 (1.56 MB)
2 Data Exploration.mp4 (8.98 MB)
3 Data Cleaning.mp4 (6.71 MB)
8 Summary.mp4 (1.24 MB)
1 Overview.mp4 (1.3 MB)
2 Content-based Recommendation Systems.mp4 (4.64 MB)
3 Context-aware Recommendation Systems.mp4 (3.49 MB)
4 Model-based Recommendation Systems.mp4 (3.59 MB)
5 Hybrid Recommendation Systems.mp4 (3.16 MB)
6 Summary.mp4 (2.25 MB)
1 Course Overview.mp4 (3.03 MB)
1 Introduction.mp4 (886.39 KB)
2 What Is Deep Learning.mp4 (2.54 MB)
3 Deep Learning Use Cases.mp4 (4.06 MB)
4 What Are Neural Networks.mp4 (4.34 MB)
5 Challenges in Designing a Deep Learning Solution.mp4 (1.94 MB)
6 What Is Data Normalization.mp4 (2.48 MB)
7 Normalization Demo.mp4 (4.65 MB)
8 Conclusion.mp4 (933.87 KB)
1 Introduction.mp4 (1.14 MB)
2 Batch Normalization.mp4 (6.96 MB)
3 Convolutional Neural Network.mp4 (6.95 MB)
4 Layer Normalization.mp4 (2.83 MB)
5 Instance Normalization.mp4 (4.1 MB)
6 Group Normalization.mp4 (3.56 MB)
7 Conclusion.mp4 (921.52 KB)
1 Introduction.mp4 (982.2 KB)
2 Quick Overview.mp4 (883.53 KB)
4 Conclusion.mp4 (1.73 MB)]
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