An Introduction To Deep Learning & Computer Vision

This course will get you started on two of the hottest topics in Machine Learning

 

What's Inside

Course Description

Deep Learning is one of the hottest buzzwords out there in Machine Learning today - this class will get beyond the hype, and help you understand what it's all about! And along the way, you will write a Python program that recognizes handwritten digits!

Prerequisites: No prerequisites, knowledge of some undergraduate level mathematics would help but is not mandatory. Working knowledge of Python would be helpful if you want to run the source code that is provided.

Taught by a Stanford-educated, ex-Googler and an IIT, IIM - educated ex-Flipkart lead analyst. This team has decades of practical experience in quant trading, analytics and e-commerce.

  • Deep Learning Networks are the cutting edge solution for the handwritten digit recognition problem and many others in computer vision. These are often large artificial neural networks.
  • A quick introduction to Computer Vision, and one of the most popular starter problems - identifying handwritten digits using the MNIST database. We also talk about feature extraction from images.
  • Perceptron Reintroduced: The perceptron is the simplest of artificial neural networks - it becomes a building block for other complex networks

Python Activity: Simple Handwriting Recognition

  • Train a neural network to classify handwritten digits in Python. First start by downloading and unzipping the MNIST database images to create some training and test datasets.
  • Then we build a neural network and specify the training process.
  • We now have a trained neural network, feed it some test data and check the accuracy.

Mail us about anything, and we will always reply :-)

What are the requirements?

  • No prerequisites, knowledge of some undergraduate level mathematics would help but is not mandatory. Working knowledge of Python would be helpful if you want to run the source code that is provided.

What am I going to get from this course?

  • Over 9 lectures and 2 hours of content!
  • Design and Implement a simple computer vision use-case: digit recognition
  • Grasp the theory underlying deep learning and computer vision
  • Confidently move on to more complex and comprehensive material on these topics
  • Understand use-cases for computer vision as well as deep learning

What is the target audience?

  • Nope! Please don't enroll for this class if you have already enrolled for our 21-hour course 'From 0 to 1: Machine Learning and NLP in Python'
  • Yep! Analytics professionals, modelers, big data professionals who haven't had exposure to machine learning
  • Yep! Engineers who want to understand or learn machine learning and apply it to problems they are solving
  • Yep! Product managers who want to have intelligent conversations with data scientists and engineers about machine learning
  • Yep! Tech executives and investors who are interested in big data, machine learning or natural language processing
  • Yep! MBA graduates or business professionals who are looking to move to a heavily quantitative role

Get started now!



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Your Instructor
Loonycorn

Loonycorn is comprised of a couple of individuals —Janani Ravi and Vitthal Srinivasan—who have honed their tech expertises at Google and Stanford. The team believes it has distilled the instruction of complicated tech concepts into funny, practical, engaging courses, and is excited to be sharing its content with eager students.

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