Learning Management
Learning Path: R: Master Data Mining Techniques with R
The world is emitting data at a very high pace and everyone wants to gain insights from the huge number of data coming their way. Data mining provides a way of finding these insights and R has become the go-to-tool for it among the data analysts and data scientists. If you're looking forward to working on complex data mining projects and gaining deeper insights of data, then go for this Learning Path. 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. Let's get on this data mining journey together!
Simple Linear Regression Basics using R Udemy
This is an introductory course to Simple Linear Regression, one of the most basic courses in Statistics. This course is most suitable for students of professionals with basic knowledge or beginning level in Statistics and R coding. It also fits for anybody who want to explore the field of statistics using R in any discipline. We will start with an introduction section where I will explain the regression equation with a detailed example. Next, we will cover the essentials of modeling.
More Data Mining with R Udemy
In data mining and association rule learning, lift is a measure of the performance of a targeting model (association rule) at predicting or classifying cases as having an enhanced response (with respect to the population as a whole), measured against a random choice targeting model. A targeting model is doing a good job if the response within the target is much better than the average for the population as a whole. Lift is simply the ratio of these values: target response divided by average response. For example, suppose a population has an average response rate of 5%, but a certain model (or rule) has identified a segment with a response rate of 20%. Then that segment would have a lift of 4.0 (20%/5%).
Robotics: Capstone Coursera
About this course: In our 6 week Robotics Capstone, we will give you a chance to implement a solution for a real world problem based on the content you learnt from the courses in your robotics specialization. It will also give you a chance to use mathematical and programming methods that researchers use in robotics labs. You will choose from two tracks - In the simulation track, you will use Matlab to simulate a mobile inverted pendulum or MIP. The material required for this capstone track is based on courses in mobility, aerial robotics, and estimation. In the hardware track you will need to purchase and assemble a rover kit, a raspberry pi, a pi camera, and IMU to allow your rover to navigate autonomously through your own environment Hands-on programming experience will demonstrate that you have acquired the foundations of robot movement, planning, and perception, and that you are able to translate them to a variety of practical applications in real world problems.
Behaviour Patterns with Machine Learning Techniques
Nowadays web-sites needs to handle huge amount of traffic. We can leverage that fact and capture user interactions with the application. Next, we can analyze users behavior and capture patterns on which we are able to react properly. In applications that needs to deal with huge amount of traffic it is very hard to detect anomalies. We'll learn how to apply clustering to find anomalies in web traffic.
Machine Learning with TensorFlow for Business Intelligence
The best job to have in 2017 according to Glassdoor? The #1 skill you need to start a career in Data Science? So, if you are interested in a career in data science, algorithmic trading, robotics, or any industry where human labor is getting replaced by machines, you have come to the right place! We have prepared an amazing course not only to get you acquainted with, but help you understand how deep machine learning works! Worried you have no experience?
Machine Learning Made Easy : Beginner to Advanced using R
Want to know how Machine Learning algorithms work and how people apply it to solve data science problems? You are looking at right course! This course has been created, designed and assembled by professional Data Scientists who have worked in this field for nearly a decade. We can help you understand the complex machine learning algorithms while keeping you grounded to the implementation on real business and data science problems. We will let you feel the water and coach you to become a full swimmer in the realm of data science and Machine Learning.
Speed Reading Memory: Become A Learning Machine & Read Fast
You learn important information on a daily basis, either to gain knowledge or for school, but you are losing a lot of this useful information because you didn't learn it properly in the first place It doesn't have to stay this way. My complete Learning Strategy & Speed Reading course will show you the exact techniques and strategies you need to learn the right way and gain knowledge or remember important information easily. For less than a movie ticket, you will get over 4 hours of video lectures and the freedom to ask me any questions regarding the course as you go through it. What Is In This Course? Your Learning and Reading Sessions Will Never Be The Same.
Journey from Statistics to Machine Learning Udemy
Complex statistics in Machine Learning worry a lot of developers. Knowing statistics helps you build strong Machine Learning models that are optimized for a given problem statement. This video will teach you all it takes to perform complex statistical computations required for Machine Learning. Understand the real-world examples that discuss the statistical side of Machine Learning and familiarize yourself with it. We will discuss the application of frequently used algorithms on various domain problems, using both Python and R programming.
A-Z Machine Learning using Azure Machine Learning (AzureML)
In this lecture, we will learn how to predict an outcome that can have multiple values. We are going to use the wine quality dataset and predict the quality of wine based on various characteristics or physiochemical properties of wine, that may affect its quality, such s the acidity, citric acid, residual sugar in it, density and so on.