**1. Introduction to Neural Networks**- Introduction to Neural Network
- Introduction to Perceptron
- Activation Functions
- Cost Functions
- Gradient Decent
- Stochastic Gradient Descent
- Back propagation

**2. Deep Frameworks**

- Installing Tensorflow and Keras
- Tensorflow and Keras Basic Syntax
- Tensorflow Graphs
- Variables and Placeholder
- Saving and Restoring Models
- Tensorboard

**3. Artificial Neural Network with Tensorflow**

- Neural Network for Regression
- Neural Network for Classification
- Evaluating the ANN
- Improving and tuning the ANN

**4. Convolution Neural Networks**

- Convolution Operation
- ReLU Layer
- Pooling
- Flattening
- Full Connection
- Softmax and Cross Entropy

**Case Studies:**

**5. Keras (Backend Tensorflow)**

- Keras vs Tensorflow
- Introduction to Keras
- Building Artificial Neural Network with Keras
- Building Convolution Neural Network with Keras

**Projects**

Face Recognition project gives details of the person and can recognize the gender and names. This project involves in

- Collection of images
- Preprocessing the data
- Applying the Model (Machine Learning or Deep Learning)
- Training and Testing using the model

**Ex: **Security Unlock, Gender Recognition, Identity Recognition** **

Virtual Assistants are now a common requirement for an Organization. But, to make the assistant more effective we are now into the chatbots which involves Natural Language Process, Deep Learning and Artificial Intelligence. This interactive chatbots are designed to serve as an intellectual responsive process.

** Ex: **Alexa, Siri, Google Assistant