As we approach 2017, we have compiled a list of the most popular data science, machine learning, deep learning and related articles published on DSC in 2016. Many great articles have not been included yet as they are very recent, but I have no doubt that they will make it to the top when we will publish our 2017 selection. Also, click here to check out the best articles of 2015.
Top 30 articles
- 12 Algorithms Every Data Scientist Should Know
- 40 Techniques Used by Data Scientists
- 15 Deep Learning Libraries
- Data scientist paid $500k can barely code!
- The New Rules for Becoming a Data Scientist
- Learning R in Seven Simple Steps
- Hitchhiker’s Guide to Data Science, Machine Learning, R, Python
- 24 Uses of Statistical Modeling (Part I)
- The Death of the Statistical Tests of Hypotheses
- 11 Important Model Evaluation Techniques Everyone Should Know
- 48 Questions to Ask to a Potential Data Scientist Hire
- What pays most: R, Python, or SQL?
- 33 unusual problems that can be solved with data science
- 5 Excel Add Ins Every Data Scientist Should Install
- 5 Free Data Science eBooks For Your Summer Reading List
- Java versus Python
- A Complete Tutorial to Learn Data Science with Python from Scratch
- 12 Python Resources for Data Science
- What statisticians think about data scientists
- The Guide to Learning Python for Data Science
- How Bayesian Inference Works
- A Cheat Sheet on Probability
- Write Code to Rewrite Your Code: jscodeshift
- Top 20 Big Data Experts to Follow (Includes Scoring Algorithm)
- 10 Deep Learning Terms Explained in Simple English
- Scikit-Learn Tutorial Series
- Top 10 IPython Tutorials for Data Science and Machine Learning
- Implementation of 17 classification algorithms in R
- Top 10 Machine Learning Algorithms
Top DSC Resources
- Article: What is Data Science? 24 Fundamental Articles Answering This Question
- Article: Hitchhiker’s Guide to Data Science, Machine Learning, R, Python
- Tutorial: Data Science Cheat Sheet
- Tutorial: How to Become a Data Scientist – On Your Own
- Categories: Data Science – Machine Learning – AI – IoT – Deep Learning
- Tools: Hadoop – DataViZ – Python – R – SQL – Excel
- Techniques: Clustering – Regression – SVM – Neural Nets – Ensembles – Decision Trees
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