Neural Networks (ANN) using Keras and TensorFlow 2.0 in Python by Start-Tech Academy

Neural Networks (ANN) using Keras and TensorFlow 2.0 in Python

What's included?

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Contents

Introduction
Welcome to the Course
3 mins
Introduction to Neural Networks and Course flow
5 mins
Course Resourses
10.5 MB
Setting up Python and Jupyter Notebook
Installing Python and Anaconda
4 mins
Opening Jupyter Notebook
10 mins
Introduction to Jupyter
14 mins
Arithmetic operators in Python Python Basics
5 mins
Strings in Python Python Basics
20 mins
Lists Tuples and Directories Python Basics
19 mins
Working with Numpy Library of Python
12 mins
Working with Pandas Library of Python
10 mins
Working with Seaborn Library of Python
9 mins
Single Cells - Perceptron and Sigmoid Neuron
Perceptron
10 mins
Activation Functions
8 mins
Creating Perceptron model
15 mins
Creating a network and training it
Basic Terminologies
10 mins
Gradient Descent
13 mins
Back Propagation
23 mins
Some Important Concepts
13 mins
Hyperparameters
9 mins
Keras and Tensorflow
4 mins
Building ANN models in Python
Installing Tensorflow and Keras
5 mins
Dataset for classification
8 mins
Normalization and Test-Train split
6 mins
Different ways to create ANN using Keras
2 mins
Building the Neural Network using Keras
13 mins
Compiling and Training the Neural Network model
11 mins
Evaluating performance and Predicting using Keras
10 mins
Building Neural Network for Regression Problem
23 mins
Using Functional API for complex architectures
13 mins
Saving - Restoring models and Using Callbacks
20 mins