World's Best AI Learning Platform with profoundly Demanding Certification Programs
Designed by IITian's, only for AI Learners.
Posted on August 27, 2015
Games are played with a strategy. Every player or team would make a strategy before starting the game and they have to change or build a new strategy according to the current situation(s) in the game.
In this post, I'll discuss considerations for normalizing your data - with a specific focus on neural networks. In order to understand the concepts discussed, it's important to have an understanding of gradient descent.
Scatter plots are used to plot data points on horizontal and vertical axis in the attempt to show how much one variable is affected by another. Each row in the data table is represented by a marker the position depends on its values in the columns set on the X and Y axes. A third variable can be set to correspond to the color or size of the markers, thus adding yet another dimension to the plot.
Violin plots are similar to box plots, but they also show at different values ,the probability density of data.A marker for the median of the data and a box indicating the interquartile range are included in these plots, as in the standard box plots. Overlaid on this box plot is a kernel density estimation. It used to represent comparison of a variable distribution (or sample distribution) across different "categories".
I would say that my data science learning path was fairly traditional. I did my undergrad in economics and have master’s degrees in global commerce and computer science (concentration in machine learning and artificial intelligence). I learned my business acumen from my coursework during my commerce degree and picked up most of the technical elements from my master’s in CS. I had a data science internship, and I was on my way.
It is all well and good to learn the technical skills that you need to become a data scientist. I think that it is also extremely important to learn to think like a data scientist. That means always questioning…basically everything
(Mo-Cap, for short) is the process of recording with camera real-life movements of people for the purpose of recreating those exact movements in a computer generated scene. As someone who is fascinated by the use of this tech in game development for creating animations, I was thrilled to see the massive improvements brought to this tech with the help of Deep Learning.
Artificial Intelligence which is also called natural language processing (NLP) and is being used by the branch to automate document processing, analysis, and customer service activities. Three applications include:
Computer vision is concerned with modeling and replicating human vision using computer software and hardware. In this chapter, you will learn in detail about this.