Top October Stories: Top 10 Machine Learning Algorithms for Beginners

For the month of October, we also recognize the most popular posts and blogger based on unique page views (UPV) and social shares.

Most Viewed - Platinum Badge
(>24,000 views)

1. Top 10 Machine Learning Algorithms for Beginners, by Reena Shaw (*)

 

Most Viewed - Gold Badges (>12,000 UPV)

2. Understanding Machine Learning Algorithms, by Brett Wujek
3. Want to Become a Data Scientist? Read This Interview First, by Kevin Gray

Most Viewed - Silver Badges (> 6,000 UPV)

4. 7 Types of Artificial Neural Networks for Natural Language Processing, by Olga Davydova
5. Deep Learning for Object Detection: A Comprehensive Review, by Joyce Xu (*)
6. How I started with learning AI in the last 2 months, by Shival Gupta (*)
7. Learning git is not enough: becoming a data scientist after a science PhD, by Mike Lee Williams (*)
8. XGBoost, a Top Machine Learning Method on Kaggle, Explained, by Ilan Reinstein
9. AlphaGo Zero: The Most Significant Research Advance in AI, by Gregory Piatetsky (*)
10. 6 Books Every Data Scientist Should Keep Nearby, by Kayla Matthews
11. Using Machine Learning to Predict and Explain Employee Attrition, by Matt Dancho (*)
12. 7 Steps to Mastering Deep Learning with Keras, by Matthew Mayo

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Most Shared - Platinum Badge
(>2,400 shares)

1. Top 10 Machine Learning Algorithms for Beginners, by Reena Shaw

 

Most Shared - Gold Badges (>1,200 shares)

2. Understanding Machine Learning Algorithms, by Brett Wujek
3. 6 Books Every Data Scientist Should Keep Nearby, by Kayla Matthews
4. Want to Become a Data Scientist? Read This Interview First, by Kevin Gray

Most Shared - Silver Badges (>700 shares)

5. Ranking Popular Deep Learning Libraries for Data Science, by Rachel Allen and Michael Li
6. 7 Types of Artificial Neural Networks for Natural Language Processing, by Olga Davydova
7. Using Machine Learning to Predict and Explain Employee Attrition, by Matt Dancho
8. AlphaGo Zero: The Most Significant Research Advance in AI, by Gregory Piatetsky
9. XGBoost: A Concise Technical Overview, by Reena Shaw (*)
10. An Overview of 3 Popular Courses on Deep Learning, by Vishnu Subramanian.
11. XGBoost, a Top Machine Learning Method on Kaggle, Explained, by Ilan Reinstein
12. TensorFlow: Building Feed-Forward Neural Networks Step-by-Step, by Ahmed Gad
13. Deep Learning for Object Detection: A Comprehensive Review, by Joyce Xu
14. Random Forests(r), Explained, by Ilan Reinstein (*)
15. How LinkedIn Makes Personalized Recommendations via Photon-ML Machine Learning tool, by Yiming Ma, Bee-Chung Chen, and Deepak Agarwal
16. 7 Techniques to Visualize Geospatial Data, by Vasavi Ayalasomayajula (*)

(*) indicates that badge added or upgraded based on these monthly results.

Most Shareable (Viral) Blogs

Among the top blogs, here are the 5 blogs with the highest ratio of shares/unique views, which suggests that people who read it really liked it.

1. Ranking Popular Deep Learning Libraries for Data Science, by Rachel Allen and Michael Li
2. Edge Analytics - What, Why, When, Who, Where, How?, by Ramesh Dontha
3. Best practices of orchestrating Python and R code in ML projects, by Marija Ilic
4. Learn Generalized Linear Models (GLM) using R, by Chaitanya Sagar
5. How LinkedIn Makes Personalized Recommendations via Photon-ML Machine Learning tool, by Yiming Ma, Bee-Chung Chen, and Deepak Agarwal