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Beginning Scala Programming Udemy

@machinelearnbot

This Scala training course from Infinite Skills teaches you everything you need to know about the Scala programming language. This course is designed for users that already have some programming experience. You will start by learning the language basics of Scala, including sequences, recursion, and nesting functions. The course will then teach you about the object-oriented aspects of Scala, linearization of trait methods, and building and writing with XML. This video tutorial also covers text processing, parallelism and actors, and libraries for unit testing.


Using Simpson's Paradox to Discover Interesting Patterns in Behavioral Data

arXiv.org Artificial Intelligence

We describe a data-driven discovery method that leverages Simpson's paradox to uncover interesting patterns in behavioral data. Our method systematically disaggregates data to identify subgroups within a population whose behavior deviates significantly from the rest of the population. Given an outcome of interest and a set of covariates, the method follows three steps. First, it disaggregates data into subgroups, by conditioning on a particular covariate, so as minimize the variation of the outcome within the subgroups. Next, it models the outcome as a linear function of another covariate, both in the subgroups and in the aggregate data. Finally, it compares trends to identify disaggregations that produce subgroups with different behaviors from the aggregate. We illustrate the method by applying it to three real-world behavioral datasets, including Q\&A site Stack Exchange and online learning platforms Khan Academy and Duolingo.


AWS Machine Learning in Motion

#artificialintelligence

This amazing liveVideo course will put your machine learning on the fast track! AWS Machine Learning in Motion gives you a complete tour of the essential tools, techniques, and concepts you need to do complex predictions and other data analysis using the AWS machine learning services! In this interactive liveVideo course, you'll get started with cloud-based machine learning under the guidance of experienced software engineer and TED Speaker Kesha Williams. You'll cut through the theory and jargon as you build a working crime-fighting machine learning algorithm! Starting with a tour of AWS' tools and the basics of machine learning, you'll dive into the learning algorithms supported by AWS, such as linear regression, multinomial logistic regression, and logistic regression.


Python: Artificial Intelligence with Python: 3-in-1

@machinelearnbot

Artificial Intelligence is one of the hottest fields in computer science right now and has taken the world by storm as a major field of research and development. Python has surfaced as a dominant language in AI/ML programming because of its simplicity and flexibility, as well as its great support for open source libraries such as Scikit-learn, Keras, spaCy and TensorFlow. This comprehensive 3-in-1 course is designed to teach you the fundamentals of Deep Learning and use them to build intelligent systems. You'll solve real-world problems such as face detection, handwriting recognition, and more. You'll get an exposure to hands-on projects that simplify your first steps in the world of Artificial Intelligence with Python.


Deep Learning Prerequisites: Linear Regression in Python

@machinelearnbot

This course teaches you about one popular technique used in machine learning, data science and statistics: linear regression. We cover the theory from the ground up: derivation of the solution, and applications to real-world problems. We show you how one might code their own linear regression module in Python. Linear regression is the simplest machine learning model you can learn, yet there is so much depth that you'll be returning to it for years to come. In the first section, I will show you how to use 1-D linear regression to prove that Moore's Law is true.


Big Geospatial Data Analysis with Google Earth Engine

@machinelearnbot

This course provides both theoretical knowledge and practical skills in Big Geospatial Data Analysis with Google Earth Engine. In this course, you will be given hands on practical exercises to master analyzing big geospatial data on the cloud. You will learn to access, process and analyze satellite data including Landsat, MODIS, and Sentinel and others using an open source platform. You will also learn to classify satellite images using machine learning algorithms. You will also have access to the lab exercise scripts as part of this course.


Machine Learning - Fun and Easy using Python and Keras

@machinelearnbot

This course price will increase to $200 as of 1st April 2018 from $190. The price will increase regularly due to updated content. Get this course while it is still low. Welcome to the Fun and Easy Machine learning Course in Python and Keras. Are you Intrigued by the field of Machine Learning?


Cluster Analysis in Data Mining Coursera

@machinelearnbot

Course is very good I learnt about a lot of things related to clustering. Actually it is a very good introductory course in clustering compared to the resources available online in general. Apart from these things I truly enjoyed and learned many new things.


Industrial CATIA V5 R20: Deep Learning All In One from A- Z

@machinelearnbot

CATIA (Computer Aided Three-Dimensional Interactive Application) is a professional CAD / CAM-based software produced by the French company Dassault Systรจmes. Especially the automotive sector, aircraft production and other simulation sectors that can respond to the needs of the program is used more often and every sector is appealing to cutting. Almost all automotive industry in the world is using computer aided design and manufacturing. Catia ensures that the products that are to be produced can be processed in the virtual environment during the production process. After a product is designed by the designer in the Catia program, the ergonomist explores the ergonomics of the design.


Advanced AI: Deep Reinforcement Learning in Python

@machinelearnbot

This course is all about the application of deep learning and neural networks to reinforcement learning. If you've taken my first reinforcement learning class, then you know that reinforcement learning is on the bleeding edge of what we can do with AI. Specifically, the combination of deep learning with reinforcement learning has led to AlphaGo beating a world champion in the strategy game Go, it has led to self-driving cars, and it has led to machines that can play video games at a superhuman level. Reinforcement learning has been around since the 70s but none of this has been possible until now. The world is changing at a very fast pace. The state of California is changing their regulations so that self-driving car companies can test their cars without a human in the car to supervise.