Ementorhub

What you'll learn

Job-ready PyTorch skills employers need in just 6 weeks

How to implement and train linear regression models from scratch using PyTorch’s functionalities

Key concepts of logistic regression and how to apply them to classification problems

How to handle data and train models using gradient descent for optimization

Skills you'll gain

PyTorch (Machine Learning Library)

Probability & Statistics

Machine Learning

Linear Algebra

Deep Learning

Predictive Modeling

Data Manipulation

Artificial Neural Networks

Regression Analysis

There are 6 modules in this course

AI developers use PyTorch to design, train, and optimize neural networks to enable computers to perform tasks such as image recognition, natural language processing, and predictive analytics. During this course, you’ll learn about 2-D Tensors and derivatives in PyTorch. You’ll look at linear regression prediction and training and calculate loss using PyTorch. You’ll explore batch processing techniques for efficient model training, model parameters, calculating cost, and performing gradient descent in PyTorch. Plus, you’ll look at linear classifiers and logistic regression. Throughout, you’ll apply your new skills in hands-on labs, and at the end, you’ll complete a project you can talk about in interviews. If you’re an aspiring AI engineer with basic knowledge of Python and mathematical concepts, who wants to get hands-on with PyTorch, enroll today and get set to power your AI career forward!

Linear Regression

Linear Regression PyTorch Way

Multiple Input Output Linear Regression

Logistic Regression for Classification

Practice Project and Final Project