DEEP LEARNING OVERVIEW

Data Science combines statistics, scientific methods, Artificial Intelligence and Data Analysis to extract the value of data. To provide meaningful insights, data scientists employ a variety of skills to analyse data acquired from the web, smartphones, customers, sensors, and other sources. The process of cleaning, collecting, and changing data in order to undertake advanced data analysis is known as data cleansing. As a result of the vast amount of data being generated and the breakthroughs in the field of analytics, it has become a requirement for businesses. Companies from a variety of industries, including finance, marketing, retail, information technology, and banking, are working to develop the most up-to-date information. They’re all on the lookout for scientists who can provide them with knowledge. As a result, data scientists are in great demand all around the world, and it may be a good option for someone to take as a profession.

Duration: 60 hours

Course Content:

1. Introduction to Deep Learning

• Difference Between Artificial Intelligence vs Machine Learning vs Deep Learning

2. Basic Neural Network

• Difference between ANN and BNN
• Single Layer Perceptron in TensorFlow
• Multi-Layer Perceptron Learning in Tensorflow
• Deep Neural net with forward and back propagation from scratch - Python
• ML - List of Deep Learning Layers
• Understanding Multi-Layer Feed Forward Networks

3.Activation Functions

• Activation Functions
• Types Of Activation Function in ANN
• Activation Functions in Pytorch
• Understanding Activation Functions in Depth

4. Artificial Neural Network

• Artificial Neural Networks and its Applications
• Gradient Descent Optimization in Tensorflow
• Choose optimal number of epochs to train a neural network in Keras

6. Classification

• Python | Classify Handwritten Digits with Tensorflow
• Train a Deep Learning Model With Pytorch

5. Regression

• Linear Regression using PyTorch
• Linear Regression Using Tensorflow

5. Hyperparameter tuning

• Hyperparameter tuning
• Digital Image Processing Basics
• Difference between Image Processing and Computer Vision
• CNN | Introduction to Pooling Layer
• CIFAR-10 Image Classification in TensorFlow
• Implementation of a CNN based Image Classifier using PyTorch
• Convolutional Neural Network (CNN) Architectures
• Object Detection vs Object Recognition vs Image Segmentation
• YOLO v2 - Object Detection

5. Recurrent Neural Network

• Natural Language Processing (NLP) Tutorial
• Introduction to NLTK: Tokenization, Stemming, Lemmatization, POS Tagging
• Word Embeddings in NLP
• Introduction to Recurrent Neural Network
• Recurrent Neural Networks Explanation
• Sentiment Analysis with an Recurrent Neural Networks (RNN)
• Short term Memory
• Deep Learning | Introduction to Long Short Term Memory
• Long Short Term Memory Networks Explanation
• LSTM - Derivation of Back propagation through time
• Text Generation using Recurrent Long Short Term Memory Network

5. Gated Recurrent Unit Networks

• Gated Recurrent Unit Networks
• Text Generation using Gated Recurrent Unit Networks

5. Generative Learning

• >Auto-Encoders
• How Autoencoders works ?
• Variational AutoEncoders
• Contractive Autoencoder (CAE)
• AutoEncoder with TensorFlow 2.0
• Implementing an Autoencoder in PyTorch

5. Generative adversarial networks

• Basics of Generative Adversarial Networks (GANs)
• Generative Adversarial Network (GAN)
• Use Cases of Generative Adversarial Networks
• Building a Generative Adversarial Network using Keras
• Cycle Generative Adversarial Network (CycleGAN)
• StyleGAN - Style Generative Adversarial Networks

5.Reinforcement Learning

• Understanding Reinforcement Learning in-depth
• Introduction to Thompson Sampling | Reinforcement Learning
• Markov Decision Process
• Bellman Equation
• Meta-Learning in Machine Learning

5.Q-Learning in Python

• Q-Learning in Python
• Reinforcement Learning Algorithm : Python Implementation using Q-learning

5.Deep Q Learning

• Deep Q Learning
• Implementing Deep Q-Learning using Tensorflow
• AI Driven Snake Game using Deep Q Learning

To Register For Machine Learning Training Click here

We are the best training center for Machine Learning in Greater Noida