Computational Neuroscience Coursera

@machinelearnbot

This course provides an introduction to basic computational methods for understanding what nervous systems do and for determining how they function. We will explore the computational principles governing various aspects of vision, sensory-motor control, learning, and memory. Specific topics that will be covered include representation of information by spiking neurons, processing of information in neural networks, and algorithms for adaptation and learning. We will make use of Matlab/Octave/Python demonstrations and exercises to gain a deeper understanding of concepts and methods introduced in the course. The course is primarily aimed at third- or fourth-year undergraduates and beginning graduate students, as well as professionals and distance learners interested in learning how the brain processes information.



Learn Programming in Python With the Power of Animation

@machinelearnbot

Python is a great language to master! I know that the process of learning programming can be difficult and frustrating. For this reason, we decided to develop a different learning experience for you. Instead of just programming Python on a screen, we use the power of animation in order to analyze the basic ideas. At the same time, I use a digital pen in order to develop the solution of the problem for you.


Learn programming in R Udemy

@machinelearnbot

Businesses around the world are having a need to understand how they are performing. This need has created a huge opportunity for people who are specialized in performing the Business Analysis tasks. It has been observed that now there exists a huge gap between demand and supply of the specialized workforce who is pretty much capable of handling the Business Analysis and who can quickly deliver the insights to the Business Managers.


Learning Maths for Machine Learning and Deep Learning

#artificialintelligence

While I did learn a lot of maths while doing my engineering degree, I forgot most of it by the time I wanted to get into Machine Learning. After I graduated I never really had a need for any of the maths. I did a lot of web programming which relied on logic and I can honestly say that with each system with the word'Management' in the title I lost a third of my math knowledge! I've programmed extensions for Learning Management Systems, Content Management Systems and Customer Relationship Management Systems -- I'll leave you to figure out how much math apptitude I had after working with these systems. At the moment I've got good data science skills and can use a variety of ML and DL algorithms.