This repository is a brain dump for the vast source of data science/analytic blogs and tutorials that I find helpful. Feel free to share ones that you think are interesting!
https://www.analyticsvidhya.com/blog/
For me this is by far the most visited web site to read up on a particular method, algorithm, or computing library. They have bloggers with diverse set of expertise in data science, and they have sections devoted to learning R, Python, Weka, Tableau and D3! What I like about this blog is that topics range from beginner to advanced. It's easy to get addicted to the content and spend hours on this blog.
Kaggle is truly a treasure trove for data science and machine learning. I've learned so much from working on competition and reading the forum discussion. What's nice about the Kaggle blog is they interview winners or top performers and they spill the beans on the algorithms they used to achieve top ranking score. Interestingly, I've noticed alot of model stacking for regression problems.
This blog by Christopher Olah is a gem in explaining deep learning principles starting from the Neural Network building block to the more advanced methods like Convolutional Neural Network, LSTM and Augmented Recurrent Neural Network. Olah's schematics are clean and informative, and his writings are concise. This is definitely one of the best blogs on deep learning.
This blog is geared towards more advanced deep learning algorithm, although sometimes it does talk about more fundamental stuff like 'why momentum works [in optimization]' and visualizing features within a neural network. The authors do a great job explaining how a deep learning model works with beautiful graphics.
http://online.cambridgecoding.com/quick-courses
This is a very Python-centric web portal that offers quick tutorials targeted at beginners or intermediate users in Python. The topics range from finding the best beer to Panda tricks every Data Scientist should know to analyzing genetic ancestry with 23AndMe data. Each post is concise, and it offers detailed Python script. Great for beginner in Machine Learning and Python.
https://www.dataquest.io/blog/
This is a blog written by Vik Paruchuri, a data scientist based in SF. He writes a post about twice a month to cover a particular topic. It has many useful tips, and he explains things very clearly and does example problem in Python code (mostly). I think this blog offers a glimps of the concrete skills companies are looking for in a data scientist.
I learned to do my first Kaggle data analysis by reading from this blog! It's got a quirky vibe and the blog talks about diverse range of topics (including software accessories in doing machine learning).
http://blog.christianperone.com/
In describing machine learning as the "Unknown Land", Christiane dives into advanced topics such as Deep learning, extracting hypercolumns in Convolutional Neural Net, and Genetic Algorithm.
https://sebastianraschka.com/blog/index.html
This guy wrote books on machine learning and explains the assortment of methods in Python. His blog post goes into great depth in explaining a topic, talks alot about theories too. Great source of material to gain a deeper understanding.