My recommendations – SlideShare Presentations on Data Science

Kunal Jain 11 Dec, 2015 • 3 min read


Every one has their own learning sytle! If you need close hand holding and guidance – an easy going MOOC is probably the best place to start. However, if you are a quick learner and don’t need some one to explain a lot of context, some one who prefers to glance through concepts, apply them a bit and then again refer back to these concepts – presentations can be really handy!

The beauty about learning from presentations is that you can quickly zoom in on the section you want to and come out at your own pace – no one decides that for you! If it fits your learning style, they can be the quickest way of learning a new concept in data science, even faster than videos & blogs. These presentations allow you to achieve much more in less time. So, here is a list of some best data science presentations I have come across on SlideShare.

top slideshare presentations on data science


How can you learn from these Presentations?

Among all forms of media, presentations are probably the most crisp & to the point! You can use them in multiple ways:

  1. If you already know a concept, you can quickly revise them.
  2. If you don’t know a concept, you can quickly grab basic knowledge about them.
  3. If you are fed up of video buffering and reading lengthy articles, here’s the wittiest version of them.

Just like our gigantic universe is composed of several heavenly bodies, data science is composed of several disciplines which completes its universe. I’ve categorized the presentations in following segments:

  1. Data Science, in general
  2. Machine Learning
  3. Neural Networks & Deep Learning
  4. Data Science Competitions

Note: These presentations have been shortlisted on the basis of their relevancy and views. You are free to access the list in any way sequence you wish. These presentations are in no order.


Data Science, in General

How to Become a Data Scientist?

Views – 51,469


Data By The People, For The People

Views – 17,053


The Science of Managing Data Scientists

Views – 64,302


What does a Data Scientist do?

Views – 81,156


A Statistician View on Big Data and Data Science

Views – 36,305


Myths and Mathematical Superpowers of Data Scientists

View – 42,095


How to Interview a Data Scientist?

View – 68,565


Let’s get a bit technical now!

Machine Learning

Introduction to Machine Learning

Views – 102,230


Introduction to Supervised Machine Learning and Pattern Classification

Views – 14,677


Machine Learning and Hadoop

Views – 17,822


Machine Learning and Data Mining: 12 Classification Rules

Views – 19,503


Machine Learning and Mahout

Views – 40,394


10 Lessons learnt from Building Machine Learning Systems

Views – 30,750


Neural Networks & Deep Learning

Deep Neural Networks

Views – 24,610


Neural Network and its Applications

Views – 59,550


Introduction to Artificial Neural Networks

Views – 43,554


Artificial Intelligence

Views – 40,180


Tutorial on Deep Learning

Views – 14730


Tutorials on Deep Learning and Applications

Views – Uploaded Recently


Deep Learning for Natural Language Processing

Views – Uploaded Recently

Hands on Deep Learning in Python

Views – Uploaded Recently


Data Science Competitions

Tips For Winning Data Science Competitions

Views – 9010


10 R Packages to Win Kaggle Competitions

Views – 53, 828


Not a presentation person? You can learn from YouTube videos, GitHub tutorials, data science books, reddit discussions, data science bootcamps and what not! Yet, here’s another surprise for you.


End Notes

I enjoyed curating this list and wanted to add more presentations to this list, but I realized that the list is getting too lengthy. Not to worry, I’ll surely add it in my next article.  In this article, I have enlisted useful resources (presentations) in Machine Learning, Deep Learning, Neural Networks and Deep Learning.

This isn’t an exhaustive list. This list comprises of my most liked presentations. If you wish to recommend me any useful presentation on slideshare which I might have missed, feel free to share it with me in the comments section.

Did you find this article helpful? Please share your opinions / thoughts in the comments section below.

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Kunal Jain 11 Dec 2015

Kunal is a post graduate from IIT Bombay in Aerospace Engineering. He has spent more than 10 years in field of Data Science. His work experience ranges from mature markets like UK to a developing market like India. During this period he has lead teams of various sizes and has worked on various tools like SAS, SPSS, Qlikview, R, Python and Matlab.

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