Most Popular Last Week

1. Nine Tools I Wish I Mastered Before My PhD in Machine Learning, by Aliaksei Mikhailiuk
2. How to be a Data Scientist without a STEM degree, by Terence Shin
3. Data Scientists Without Data Engineering Skills Will Face the Harsh Truth, by Soner Yildirim
4. 20 Machine Learning Projects That Will Get You Hired, by Khushbu Shah
5. How to Find Weaknesses in your Machine Learning Models, by Michael Berk

Most Shared Last Week

1. How to Find Weaknesses in your Machine Learning Models, by Michael Berk
2. How to be a Data Scientist without a STEM degree, by Terence Shin
3. 20 Machine Learning Projects That Will Get You Hired, by Khushbu Shah
4. A Breakdown of Deep Learning Frameworks, by Kevin Vu
5. Nine Tools I Wish I Mastered Before My PhD in Machine Learning, by Aliaksei Mikhailiuk

Most Popular Tweets Last Week

1. Big Tech & Their Favourite #DeepLearning Techniques @Analyticsindiam
2. 100+ Most Valuable Github Repositories For #MachineLearning
3. The State of Data Engineering in 2021 by @datawhisp
4. Data Preparation in SQL, with Cheat Sheet! #KDN
5. Don’t Touch a Dataset Without Asking These 10 Questions – KDnuggets

Most Popular Past 30 Days

1. Do You Read Excel Files with Python? There is a 1000x Faster Way, by Nicolas Vandeput
2. Data Scientists Without Data Engineering Skills Will Face the Harsh Truth, by Soner Yildirim
3. A Data Science Portfolio That Will Land You The Job, by Natassha Selvaraj
4. Automate Microsoft Excel and Word Using Python, by Mohammad Khorasani
5. How to Create Stunning Web Apps for your Data Science Projects, by Murallie Thuwarakesh

Most Shared Past 30 Days

1. How To Deal With Imbalanced Classification, Without Re-balancing the Data, by David B Rosen (PhD)
2. How to Find Weaknesses in your Machine Learning Models, by Michael Berk
3. The Machine & Deep Learning Compendium Open Book, by Ori Cohen
4. Data Scientists Without Data Engineering Skills Will Face the Harsh Truth, by Soner Yildirim
5. Hypothesis Testing Explained, by Angelica Lo Duca