Course duration: Nov 14, 2020 - Dec 26, 2020 (tentative)
“Deep Learning with PyTorch: Zero to GANs” is an online course intended to provide a coding-first introduction to deep learning using the PyTorch framework. The course takes a hands-on coding-focused approach and will be taught using live interactive Jupyter notebooks, allowing students to follow along and experiment. Theoretical concepts will be explained in simple terms using code. Participants will receive weekly assignments and work on a project with real-world dataset to test their skills. Upon successful completion of the course, participants will receive a certificate of completion.
The objective of this assignment is to develop a solid understanding of PyTorch tensors. In this assignment you will:
In this assignment, we’re going to use information like a person’s age, sex, BMI, no. of children, and smoking habit to predict the price of yearly medical bills. We will train a model with the following steps:
The ability to try many different neural network architectures to address a problem is what makes deep learning really powerful, especially compared to shallow learning techniques like linear regression, logistic regression etc. In this assignment, you will:
Students will participate in a private data science competition hosted on the Kaggle platform. The competition will run for 3 weeks, allowing students to apply & improve their skills in a competitive environment. Students will gain exposure to working with cloud GPU platforms.
For the course project, students will create an image classification model using Convolutional neural networks, on a real-world dataset of their choice. The project will allow students to experiment with different types of models and regularization techniques. Students will also present their work at the end of the course and publish a blog post describing their approach and results.
Participants who register for the course and make valid submissions for all assignments will be eligible to receive a Certificate of Completion by Jovian. Selected projects will also be receive a Best Project Award based on evaluation criteria determined by the instructors.
Aakash is the co-founder and CEO of Jovian, a project management and collaboration platform for machine learning. Prior to starting Jovian, Aakash worked as a software engineer (APIs & Data Platforms) at Twitter in Ireland & San Francisco and graduated from Indian Institute of Technology, Bombay. He’s also an avid blogger, open source contributor and online educator. https://www.linkedin.com/in/aakashns/