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AI WITH MACHINE & DEEP LEARNING

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Introduction with Artificial Intelligence.

  • What is AI (Artificial Intelligence) ?
  • What types of intelligences we are talking about?
  • Different definitions and Ultimate goal of AI.
  • What are application areas for AI?
  • History of AI and some real life examples of AI.

ML and other related terms to AI.

  • What is ML and How it is related with AI?
  • What is NLP and How it is related with AI?
  • What is DL and How it is related with ML and AI?
  • What are ANNs and DNNs and How are they related to AI?

A working example of AI and ML.

Project 1 – These simple tasks are to make you understand how AI and ML can find their applications in real life.

Python libraries for ML.

  • What are Libraries, packages and Modules?
  • What are top Python libraries for ML in Python?

Setting up Anaconda development environment.

  • Why choosing Anaconda development environment?
  • Setting up Anaconda development environment on Windows 10 PC.
  • Verifying proper installation of Anaconda environment.

Getting into core development of ML.

  • What is a classifier in ML?
  • Important elements and flow of any ML projects.
  • Let’s develop our first ML program – explanations
  • Let’s develop our first ML program – development

Project – 2

These simple tasks are going to give you some great experience with Machine Learning introductory programs or better say, “Hello world” programs of Machine Learning.

Different ML techniques.

  • What all ML techniques are there?
  • Evaluation methods of all ML techniques.

(IRIS flower project) Developing complete project of ML.

  • Developing complete ML project – understanding data set
  • Developing complete ML project – understanding flow of project
  • Developing complete ML project – visualizing data set through Python
  • Developing complete ML project – development
  • Developing complete ML project – concepts explanations
  • –(Digit recognition project) Developing another project of ML.

Project 3

  • After completing these project, you have done and understood multiple complete projects of Machine Learning.

Introduction of Ai with Deep Learning

  • Installation
  • CPU Software Requirements
  • CPU Installation of PyTorch
  • PyTorch with GPU on AWS
  • PyTorch with GPU on Linux
  • PyTorch with GPU on MacOSX

PyTorch Fundamentals: Matrices

  • Matrix Basics
  • Seed for Reproducibility
  • Torch to NumPy Bridge
  • NumPy to Torch Bridge
  • GPU and CPU Toggling
  • Basic Mathematical Tensor Operations
  • Summary of Matrices

PyTorch Fundamentals: Variables and Gradients

  • Variables
  • Gradients
  • Summary of Variables and Gradients

Linear Regression with PyTorch

  • Linear Regression Introduction
  • Linear Regression in PyTorch
  • Linear Regression From CPU to GPU in PyTorch
  • Summary of Linear Regression

Logistic Regression with PyTorch

  • Logistic Regression Introduction
  • Linear Regression Problems
  • Logistic Regression In-depth
  • Logistic Regression with PyTorch
  • Logistic Regression From CPU to GPU in PyTorch
  • Summary of Logistic Regression

Feedforward Neural Network with PyTorch

  • Logistic Regression Transition to Feedforward Neural Network
  • Non-linearity
  • Feedforward Neural Network in PyTorch
  • More Feedforward Neural Network Models in PyTorch
  • Feedforward Neural Network From CPU to GPU in PyTorch
  • Summary of Feedforward Neural Network

Convolutional Neural Network (CNN) with PyTorch

  • Feedforward Neural Network Transition to CNN
  • One Convolutional Layer, Input Depth of 1
  • One Convolutional Layer, Input Depth of 3
  • One Convolutional Layer Summary
  • Multiple Convolutional Layers Overview
  • Pooling Layers
  • Padding for Convolutional Layers
  • Output Size Calculation
  • CNN in PyTorch
  • More CNN Models in PyTorch
  • CNN Models Summary
  • Expanding Model’s Capacity
  • CNN From CPU to GPU in PyTorch
  • Summary of CNN

Recurrent Neural Networks (RNN)

  • Introduction to RNN
  • RNN in PyTorch
  • More RNN Models in PyTorch
  • RNN From CPU to GPU in PyTorch
  • Summary of RNN

Long Short-Term Memory Networks (LSTM)

  • Introduction to LSTMs
  • LSTM Equations
  • LSTM in PyTorch
  • More LSTM Models in PyTorch
  • LSTM From CPU to GPU in PyTorch
  • Summary of LSTM

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