Course curriculum

  • 1

    Introduction

    • Course Content
    • Introduction to Instructor and Aisciences
    • Benefits of Framework
    • Installation Pytorch
  • 2

    Tensor

    • Introduction to Tensor
    • List vs Array vs Tensor
    • Arithmetic Operations
    • Tensor Operations
    • Auto-Gradiants
    • Activity Solution
    • Detaching Gradients
    • Loading GPU
  • 3

    NN with Tensor

    • Introduction to Module
    • Basic NN part 1
    • Basic NN part 2
    • Loss Functions
    • Activation Functions & Hidden Layers
    • Optimizers
    • Data Loader & Dataset
    • Activity
    • Activity Solution
    • Formating the Output
    • Graph for Loss
  • 4

    CNN

    • Introduction to Module
    • CNN vs NN
    • Introduction to Convolution
    • Convolution Animations
    • Convolution using Pytorch
    • Introduction to Pooling
    • Pooling using Numpy
    • Pooling in Pytorch
    • Introduction to Project
    • Project (Data Loading)
    • Project (Transforms)
    • Project (DataLoaders)
    • Project (CNN Architect)
    • Project (Forward Propagation)
    • Project (Training CNN)
    • Project (Analyzing Model Output)
    • Project (Making Predictions)