How to Get Hands-On With Machine Learning


Machine Learning is a new and exciting field of study that focuses on the development of computer programs that gives it the ability to think like humans and solve problems based on previous experiences.  A truly exciting technology, ML is currently being used in multiple fields and industries like entertainment, videos surveillance, spam filtering, online customer support, search engine result refining, Social Media services, etc. ML enables analysis of massive quantities of data allowing computers to tackle tasks on their own without a need for express commands.

Jigsaw academy reviews and ratings will show you as to how this reputable online training institute helps you build your career in the field of Big Data, AI and ML.


It is rightly said that best way to learn is to do it. In order to understand the full capabilities and abilities of Machine Learning (ML), you have to get hands-on with it, which is what exactly people interested a career in this fast-growing technology are doing.  The starting point of course will vary from individual to individual depending upon his/her experience, educational level, expertise and familiarity with the subject. Here we present a short list of resources with a bit of insight into their requirements and value.

Competitions

It is often seen that the mere mention of the word competition tends to scare off people. It should never be the case as competitions provide an exciting opportunity for people to get hands-on with machine learning. You can expect to find a lot of helpful resources here and if you manage to score a prominent position after getting well-versed with the subject, it can help you embellish your resume with added qualification.

Kaggle is a data science platform employed by businesses to crowd source problem-solving. If you are a member, you will be provided access to kernels, forums, blogs, job postings, free mini courses, documentations, etc.

This is what Open ML (beta 2) has to say about itself: “It is an inclusive movement to build an open, organized, online ecosystem for machine learning". It is primarily concerned with building open source tool which in turn can facilitate easy sharing of data. Participants can pull the open data into the machine learning environments they prefer to build useful models either by themselves or by enlisting help of other data scientists.

AnalyticsVidhya positions itself as "a next-gen data science ecosystem." Its website will give you access to community, tutorials, competitions, blogs, certifications and job listings.

However, participants need to be aware of the fact that many "introductory" courses are designed with the idea that the participant is not a complete novice when it comes to Machine Learning.


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