Do your non-player characters lack drive and ambition? Are they slow, stupid and constantly banging their heads against the wall? Then this course is for you. Join Penny as she explains, demonstrates and assists you to create your very own NPCs in Unity with C#. All you need is a sound knowledge of Unity, C# and the ability to add two numbers together.

Data science is an ever-evolving field, with exponentially growing popularity. Data science includes techniques and theories extracted from the fields of statistics, computer science, and most importantly machine learning, databases, and visualization. So, if you're a developer who wants to enter in the field of data science by exploring concepts of statistics, data analysis, and data mining, then follow this Learning Path. Packt's Video Learning Path is a series of individual video products put together in a logical and stepwise manner such that each video builds on the skills learned in the video before it. This Learning Path begins with explaining the steps to analyse data and identify which summary statistics are relevant to the type of data you are summarizing.

Are you interested to explore advanced algorithm concepts such as random forest vector machine, K- nearest, and more through real-world examples? Packt's Video Learning Paths are a series of individual video products put together in a logical and stepwise manner such that each video builds on the skills learned in the video before it. Machine learning and data science are some of the top buzzwords in the technical world today. Machine learning - the application and science of algorithms that makes sense of data, is the most exciting field of all the computer sciences! It explores the study and construction of algorithms that can learn from and make predictions on data.

"Honestly Mike your classes speak for themselves. They're informative, concise and just really well put together. They're exactly the kind of courses I look for." This is the second course in a series designed to prepare you for becoming a machine learning engineer. I'll keep this updated and list only the courses that are live.

This is the fourth course in the series designed to prepare you for a real world job in the machine learning space. I'd highly recommend you take the courses serially. People love building models and many think that machine learning engineers sit around and build models all day. Take the courses in order to understand what machine learning engineers really do. In this course we are going to learn SciKit-Learn using a lab integrated approach.

In this work, we propose an automated method to identify semantic bugs in student programs, called ATAS, which builds upon the recent advances in both symbolic execution and active learning. Symbolic execution is a program analysis technique which can generate test cases through symbolic constraint solving. Our method makes use of a reference implementation of the task as its sole input. We compare our method with a symbolic execution-based baseline on 6 programming tasks retrieved from CodeForces comprising a total of 23K student submissions. We show an average improvement of over 2.5x over the baseline in terms of runtime (thus making it more suitable for online evaluation), without a significant degradation in evaluation accuracy.

With this course, you'll have the keys to the entire R Machine Learning Kingdom!

MATLAB is the language of choice for many researchers and mathematics experts when it comes to machine learning. This video will help beginners build a foundation in machine learning using MATLAB. You'll start by getting your system ready with the MATLAB environment for machine learning and you'll see how to easily interact with the MATLAB workspace. You'll then move on to data cleansing, mining, and analyzing various data types in machine learning and you'll see how to display data values on a plot. Next, you'll learn about the different types of regression technique and how to apply them to your data using the MATLAB functions.

Artificial intelligence will transform many companies and create completely new types of businesses. Andrew Ng, cofounder of Coursera, AI Fund, and Landing.AI and Google Brain, shares how businesses can benefit. The interview was conducted by Michael Chui, a partner of the McKinsey Global Institute. I think it clarifies some interesting issues. Artificial intelligence (AI) is at the cutting edge of innovation.

Learn how to select features and build simpler, faster and more reliable machine learning models. This is the most comprehensive, yet easy to follow, course for feature selection available online. Throughout this course you will learn a variety of techniques used worldwide for variable selection, gathered from data competition websites and white papers, blogs and forums, and from the instructor's experience as a Data Scientist. You will have at your fingertips, altogether in one place, multiple methods that you can apply to select features from your data set. The course starts describing simple and fast methods to quickly screen the data set and remove redundant and irrelevant features.