/Deep-Learning

This repository is a related to all about Deep Learning - an A-Z guide to the world of Data Science. This supplement contains the implementation of algorithms, statistical methods and techniques (in Python)

Primary LanguageJupyter Notebook

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This repository is a related to all about Deep Learning - an A-Z guide to the world of Data Science. This supplement contains the implementation of algorithms, statistical methods and techniques (in Python)

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Course 01 - 📚🧑‍🎓📺📝Neural Networks and Deep Learning

Week 1-📚Chapter1: Introduction of Deep learning

Tutorial Video Code
🌐1-Understanding Basic Neural Networks(Tutorial) 1-2 Content 3
🌐2-Supervised Learning with Neural Networks(Tutorial) 1 Content 6
🌐3-Exploring the Different Types of Artificial Neural Networks --- ---
🌐4- Why is Deep Learning taking off? 1 ---
5-Best Free Resources to Learn Deep learning (DL) --- ---

Week 2-📚Chapter1:2 Logistic Regression as a Neural Network

Tutorial Video Code
🌐1- Binary Classification 1 Content 3
🌐2- Logistic Regression 1-2 Content 6
🌐3- Understanding the Logistic Regression Cost Function 1 ---
🌐4-Understanding the Logistic Regression Gradient Descent 1-2 ---
🌐5-Intuition about Derivatives 1 Colab icon
🌐6-Computation Graph 1-2 ---
🌐7-Derivatives with a Computation Graph 1 ---
🌐8-Logistic Regression Gradient Descent 1 ---
🌐9-Gradient Descent on m Examples 1 Colab icon

Week 3-📚Chapter 3 Python and Vectorization

Tutorial Video Code
1-Vectorization 1 Colab icon

##Alogrithems - DL0101EN-3-1-Regression-with-Keras-py-v1.0.ipynb - DL0101EN-3-2-Classification-with-Keras-py-v1.0.ipynb - Keras - Tutorial - Happy House v1.ipynb - Keras_for_Beginners_Implementing_a_Convolutional_Neural_Network - Keras_for_Beginners_Building_Your_First_Neural_Network.ipynb