Get yourself trained on Machine Learning and with this Online Training Machine Learning and R Programming for Data Science.
Online Training Machine Learning and R Programming for Data Science
Do you want to learn the technology changing the world around us?This course is for you!Funded by a #1 Mammoth Interactive Kickstarter ProjectMachine learning is bringing us self-driving cars, facial recognition and artificial intelligence. Though machine learning originated for computers, the next big wave is machine learning on MOBILE. Enroll Now in this Complete Masterclass!17.5 hours on-demand videoOffline access via the Udemy app18 Articles11 Downloadable ResourcesFull lifetime accessHave you ever thought: why cant my mobile device domore? Learn how to do just that in this Machine Learning and R Programming for Data Science!Perform handwritten digit recognition with basic and advanced MNIST projectsBuild a weather prediction projectExplore PyCharm and the Python languageExplore Android Studio and the Java languageYou will discover applications of machine learning and where we use machine learning daily! You’ll explore different machine learning mechanisms and commonly used algorithms. You’ll also explore TensorFlow, a machine learning framework.Build a simple linear regression model in PyCharm with TensorFlowLoad data locally and multiple techniques.Install packages.Handle data outliers.Use multiple linear regression and shrinkage methods.And much more!Included in this course is material for beginners to get comfortable with the interfaces. Please note that we reuse this content in similar courses because it is introductory material. You can find some material in this course in the following related courses:Hands-On Machine Learning: Learn TensorFlow, Python, & Java!Make predictions with Python machine learning for appsR Programming: Practical Data Science and Modeling!Build UI and Android Classes. Use PyCharm with TensorFlow! Code in Python, Java and R.Python 3: Flexible and comprehensive, Python is an easy-to-use language that we will use to write powerful machine learning programs and other scripts.Java 8: Object-oriented and reliable, Java is one of the most widely-used languages and has been the choice language of Android applications for years.Android Studio 3:Build Android apps by providing both graphical and programming interfaces for front and back end functionality.TensorFlow 1.4: Allows us to build computational graphs & neural networks and perform intense tasks like training and optimizing models with ease.Learn multiple linear regression, box plotting & shrinkage. And more!Enroll now to learn a massive amount of content, starting with how to load data locally, and othertechniques.You spend so much time getting your data ready in R in data science that you need a good understanding of it. You will learn data cleaning techniques, how to handle outliers, scaling data and why we scale it, and other important examples. You will learn to load and handle data in R, and much more.Advanced Functions and AbstractionYou will work through numerous examples involving decision trees, random forest, testing, SVMs with tuning, and LDA.You will learn to build advanced functions in R around training and testing. You will be a functions expert and understand abstraction. Regression, Shrinkage, and CorrelationYou will learn regression models including linear regression and quickly move into multiple linear regression, shrinkage methods like ridge and lasso. You will learn when to use and when not to use correlation with model inputs.Enroll Now While On Sale!
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As a society, we spend hundreds of billions of dollars measuring the return on our financial assets. Yet, at the same time, we still haven’t found convincing ways of measuring the return on our investments in developing people.
And I get it: If my bank account pays me 1% a year, I can measure it to the penny. We’ve been collectively trained to expect neat and precise ROI calculations on everything, so when it’s applied to something as seemingly squishy as how effectively people are learning in the workplace, the natural inclination is to throw up our hands and say it can’t be done. But we need to figure this out. In a world where skills beat capital, the winners and losers of the next 30 years will be determined by their ability to attract and develop great talent.
Fortunately, corporate learning & development (L&D), like most business functions, is evolving quickly. We can embrace some level of ambiguity and have rigor when measuring the ROI of learning. It just might look a little different than an M.B.A. would expect to see in an Excel model.