5 Best + Machine Learning Courses Training | Basic To Advanced Concepts‎

A team of 50+ global experts has done in-depth research to come up with this compilation of Best + Machine Learning Courses Training | Basic To Advanced Concepts for 2020. All these courses are available online and will help you learn and excel at Machine Learning. These are suitable for beginners, intermediate learners as well as experts. This compilation is reviewed and updated monthly. So far, 149,000+ students and professionals have benefited from it.

Best + Free Machine Learning Courses [2020] [UPDATED]

5 Best + Machine Learning Courses Training | Basic To Advanced Concepts

1. 12 Real World CaseStudies for Machine Learning

12 Real World Case Studies for Machine Learning. Master Machine Learning by getting your hands dirty on Real Life Case studies. Be A Kaggle and Industry Grandmaster

You might know the theory of Machine Learning and know how to create algorithms. But as you know you must get your hands Dirty on Real-World Case Studies. There are so many courses which teach the basic of Machine Learning But do not cover the Applications. In this course, We will Cover applications and Case Studies from the Industry.

This course will help you bridge the gap between a person who knows machine learning and a person who actually knows how to apply Machine Learning in the real world. Knowing Machine learning and Applying it in the real world is totally different.

This course will help you tackle big and complex data set and apply machine learning techniques to achieve good results. These Case Studies will also enhance your resume as you can add these to your Portfolio.

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2. Complete Python Machine Learning & Data Science for Dummies

Machine Learning and Data Science for programming beginners using python with scikit-learn, SciPy, Matplotlib & Pandas. Machine Learning with Python for Dummies. We will discuss about the overview of the course and the contents included in this course.

Artificial Intelligence, Machine Learning and Deep Learning Neural Networks are the most used terms now a days in the technology world. Its also the most mis-understood and confused terms too.

Artificial Intelligence is a broad spectrum of science which tries to make machines intelligent like humans. Machine Learning and Neural Networks are two subsets that comes under this vast machine learning platform

Lets check what’s machine learning now. Just like we human babies, we were actually in our learning phase then. We learned how to crawl, stand, walk, then speak words, then make simple sentences.. We learned from our experiences. We had many trials and errors before we learned how to walk and talk. The best trials for walking and talking which gave positive results were kept in our memory and made use later. This process is highly compared to a Machine Learning Mechanism

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3. Machine Learning Adv: Support Vector Machines (SVM) in R

Use Support Vector Machines to solve business problems and build high accuracy prediction models in R. You are looking for a complete Support Vector Machines course that teaches you everything you need to create a Support Vector Machines model in Python, right? You have found the right Support Vector Machines techniques course!

How this course will help you?

A Verifiable Certificate of Completion is presented to all students who undertake this Machine learning advanced course. If you are a business manager or an executive, or a student who wants to learn and apply machine learning in Real world problems of business, this course will give you a solid base for that by teaching you some of the advanced technique of machine learning, which are Support Vector Machines.

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4. Machine Learning Basics: Building a Regression model in R

Use Linear Regression to solve business problems and master the basics of  Machine Learning Linear Regression in R. This course covers all the steps that one should take while solving a business problem through linear regression.

Most courses only focus on teaching how to run the analysis but we believe that what happens before and after running analysis is even more important i.e. before running analysis it is very important that you have the right data and do some pre-processing on it. And after running analysis, you should be able to judge how good your model is and interpret the results to actually be able to help your business.

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5. Machine Learning Basics: Classification models in R 

Use classification to solve business problems and master the basics of Machine Learning classification in R. This course covers all the steps that one should take while solving a business problem using classification techniques. Most courses only focus on teaching how to run the analysis but we believe that what happens before and after running analysis is even more important i.e. before running analysis it is very important that you have the right data and do some pre-processing on it. And after running analysis, you should be able to judge how good your model is and interpret the results to actually be able to help your business.

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BONUS Machine Learning Deals on Eduonix

1. Mighty Machine Learning Bundle

Mighty Bundle to Learn Machine Learning Using Python and R. A mighty Bundle designed to meet all your learning need for Artificial Intelligence & Machine Learning. It is power-packed with 20 Courses having 110+ hrs of video that will teach you AI & ML from scratch. With this bundle, you will not only learn basic AI & ML but also programming with Python & R, usage of different AI & Data Science libraries, training machine learning algorithms, building various models, deep learning and so much more. Not only this, but we have also included a course dedicated entirely to mathematical foundations behind machine learning! So gear up & begin with each of the courses one by one to have a complete understanding of AI & ML.

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2. AI and Machine Learning for Professionals

Be an advance Artificial Intelligence practitioner with our unique course bundle which covers courses for students at all stages of learning. Right from the basics such as mathematical foundations and algorithmic foundations, to more complex concepts like NLP.

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