The Deep Learning and Artificial Intelligence Introductory Bundle is an eLearning bundle that consists of four courses.
The four courses build up on each other and are suitable for users of all experience levels. Knowledge of math — calculus, linear Algebra and Probability — as well as Python and Numpy is helpful though.
If you need a Python refresher, or are just getting started, check out these Python eLearning offers to get started.
- Deep Learning Prerequisites: Linear Regression in Python — Use Probability Theory to Make More Accurate Predictions & Take the First Steps Into Deep Learning
- Deep Learning Prerequisites: Logistic Regression in Python — Introduce Yourself to the Building Blocks of Neural Networks
- Data Science: Deep Learning in Python — Learn to Build the Kinds of Artificial Neural Networks That Make Google Seem to Know Everything
- Data Science: Practical Deep Learning in Theano & TensorFlow — Build & Understand Neural Networks Using Two of the Most Popular Deep Learning Techniques
Click here to open the Deep Learning and Artificial Intelligence Introductory bundle on Ghacks Deals
A follow up course, The Advanced Guide to Deep Learning and Artificial Intelligence Bundle is available as well.
Description (first course)
Deep Learning is a set of powerful algorithms that are the force behind self-driving cars, image searching, voice recognition, and many, many more applications we consider decidedly “futuristic.” One of the central foundations of deep learning is linear regression; using probability theory to gain deeper insight into the “line of best fit.” This is the first step to building machines that, in effect, act like neurons in a neural network as they learn while they’re fed more information. In this course, you’ll start with the basics of building a linear regression module in Python, and progress into practical machine learning issues that will provide the foundations for an exploration of Deep Learning.