Top Stories, Jun 12-18: Top 15 Python Libraries for Data Science in 2017; Deep Learning Papers Reading Roadmap
Tags: Top stories
Top 15 Python Libraries for Data Science in 2017; Deep Learning Papers Reading Roadmap; The Practical Importance of Feature Selection; Understanding Deep Learning Requires Re-thinking Generalization; K-means Clustering with Tableau
Most Popular Last Week
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Top 15 Python Libraries for Data Science in 2017, by Igor Bobriakov
- 6 Interesting Things You Can Do with Python on Facebook Data, by Nour Galaby
- Deep Learning Papers Reading Roadmap
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The 10 Algorithms Machine Learning Engineers Need to Know
- Data Scientist: Learn the Skills you need for free
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10 Free Must-Read Books for Machine Learning and Data Science
- Is Regression Analysis Really Machine Learning?
Most Shared Last Week
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Deep Learning Papers Reading Roadmap, by Flood Sung - Jun 13, 2017.
- Top 15 Python Libraries for Data Science in 2017, by Igor Bobriakov - Jun 13, 2017.
- The Practical Importance of Feature Selection - Jun 12, 2017.
- Understanding Deep Learning Requires Re-thinking Generalization - Jun 16, 2017.
- K-means Clustering with Tableau – Call Detail Records Example - Jun 16, 2017.
- 7 Ways to Get High-Quality Labeled Training Data at Low Cost - Jun 13, 2017.
- Medical Image Analysis with Deep Learning, Part 3 - Jun 15, 2017.
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- 6 Interesting Things You Can Do with Python on Facebook Data
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- New Leader, Trends, and Surprises in Analytics, Data Science, Machine Learning Software Poll - May 22, 2017.
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- Must-Know: What are common data quality issues for Big Data and how to handle them? - May 16, 2017.
- Machine Learning Workflows in Python from Scratch Part 1: Data Preparation - May 29, 2017.
- Deep Learning Papers Reading Roadmap - Jun 13, 2017.
- Top 15 Python Libraries for Data Science in 2017 - Jun 13, 2017.
