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Top 8 Deep Learning Concepts Every Data Science Professional Must Know
“Deep learning is making a good wave in delivering a solution to difficult problems that have been faced in the field of artificial intelligence (AI) for so many years, as quoted by Yann LeCun, Yoshua Bengio & Geoffrey Hinton.”
For a data scientist to successfully apply deep learning, they must first understand how to apply the mathematics of modeling, choose the right algorithm to fit your model to the data, and come up with the right technique to implement.
In order to get you started, we have come up with a list of deep learning algorithms needed by every data science professional.
This 26-part course consists of tutorials on how to learn web development with Django from scratch. It's designed to be very hands-on and will walk you through every step of the web development process.
The primary objectives of this course are as follows:
Set up your local development environment with Django 2.0 (or 1.11) installing instructions for Windows, OS X, and Linux.
Work on several real-world Django projects and in the process learn all of the important Django concepts including Models & the ORM, the Admin, URL resolution, Templates, Forms, Authentication (including Facebook login!), and creating APIs.
Work with different database backends including SQLite and Postgres database.
Learn how to use Git as a version control system for your code.
Deploy your applications to production usi...
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Introduction to Django
Next, you'll get your computer all set up to work with Django. You'll also learn about what Django is.
This section walks you through your first Django application. It will cover all the fundamentals of Django including Models & the ORM, the Admin, URL resolution, Templates, Forms, and the basic built-in User Authentication.
Deep Learning Research Review Week 2: Reinforcement Learning
This is the 2nd installment of a new series called Deep Learning Research Review. Every couple weeks or so, I’ll be summarizing and explaining research papers in specific subfields of deep learning. This week focuses on Reinforcement Learning.
Imagine you're blind folded in a rough terrain, and your objective is to reach the lowest altitude. One of the best and simplest strategies you can use, is to feel the ground in every direction, and take a step in the direction where the ground is descending the fastest. If you keep repeating this process, you might end up at the lake, or even better, somewhere in the huge valley.
The rough terrain is analogous to the cost function....