15 Minute Guide to Choose Effective Courses for Machine Learning and Data Science

@machinelearnbot

Bill Gates proclaimed in a recent graduation ceremony, that artificial intelligence (AI), energy, and bio science are three most exciting and rewarding career choices today's young college graduates can choose from. I have come to believe strongly that some of the most important questions of our generation - related to sustainability, energy generation and distribution, transportation, access to basic amenities of life etc., are dependent on how intelligently we can mix the the first two branches of knowledge Mr. Gates mentions. In other words, the world of physical electronics (semiconductor industry comprises a central portion of that world), must do more to embrace fully the fruits of information technology and new developments in AI or data science. I wanted to learn, but where to start? I am a semiconductor professional with 8 years of post-PhD experience in a top technology company.


Top 20 Data Science MOOCs

@machinelearnbot

Introduce yourself to the basics of data science and leave armed with practical experience extracting value from big data. This course teaches the basic techniques of data science, including both SQL and NoSQL solutions for massive data management (e.g., MapReduce and contemporaries), algorithms for data mining (e.g., clustering and association rule mining), and basic statistical modelling (e.g., linear and non-linear regression).


Top 20 Data Science MOOCs

@machinelearnbot

Introduce yourself to the basics of data science and leave armed with practical experience extracting value from big data. This course teaches the basic techniques of data science, including both SQL and NoSQL solutions for massive data management (e.g., MapReduce and contemporaries), algorithms for data mining (e.g., clustering and association rule mining), and basic statistical modelling (e.g., linear and non-linear regression).


Become the Rafael Nadal of Machine Learning – freeCodeCamp

#artificialintelligence

One year back, I was a newbie to the world of Machine Learning. I used to get overwhelmed by small decisions, like choosing the language to code with, choosing the right online courses, or choosing the correct algorithms.


The Art of Learning Data Science

@machinelearnbot

These days, I am sure 90% of LinkedIn traffic contains one of these terms: DS, ML or DL -- acronyms for Data Science, Machine Learning or Deep Learning. Beware of the cliche though: "80% of all the statistics are made on the spot". If you blinked on these acronyms perhaps you need to google a bit and then continue reading the rest of this post. This post has 2 goals. First, it attempts to put all the fellow Data Science learners at ease.