KDnuggets™ News 19:n22, Jun 12: The Modern Open-Source Data Science/Machine Learning Ecosystem; Simplifying the Data Visualisation Process in Python
The 6 tools in the modern open-source Data Science ecosystem; Simplifying the Data Visualisation Process in Python; The Infinity Stones of Data Science; Best resources for developers transitioning into data science.
Features | Tutorials | Opinions | Tops | News | Meetings | Jobs | Academic | Image of the week
Also Random Forests vs Neural Networks: Which is Better, and When?; Top 10 Statistics Mistakes Made by Data Scientists; The Infinity Stones of Data Science.
- What you need to know: The Modern Open-Source Data Science/Machine Learning Ecosystem
- PyViz: Simplifying the Data Visualisation Process in Python
- Random Forests vs Neural Networks: Which is Better, and When?
- Top 10 Statistics Mistakes Made by Data Scientists
- The Infinity Stones of Data Science
- First Speakers Announced For Data Driven Government This Fall
- If you're a developer transitioning into data science, here are your best resources
- 3 Main Approaches to Machine Learning Models
- 5 Ways to Deal with the Lack of Data in Machine Learning
- Choosing an Error Function
Jupyter Notebooks: Data Science Reporting- The Whole Data Science World in Your Hands
- Mongo DB Basics
Jupyter Notebooks: Data Science Reporting- NLP and Computer Vision Integrated
- The Data Fabric for Machine Learning Part 1-b – Deep Learning on Graphs
- A Step-by-Step Guide to Transitioning your Career to Data Science – Part 2
- Using the ‘What-If Tool’ to investigate Machine Learning models
- Top May Stories: A Step-by-Step Guide to Transitioning your Career to Data Science; 7 Steps to Mastering SQL for Data Science – 2019 Edition
- Top Stories, Jun 3 - 9: 7 Steps to Mastering Intermediate Machine Learning with Python 2019 Edition; How to choose a visualization
- Top KDnuggets Tweets, May 29 – June 4: Difference between #MachineLearning and #AI; Understanding Backpropagation as Applied to LSTM
- Proxi: Data Scientist [Berkeley, CA]
- Digible: Data Engineer [Denver, CO]
- Apple: Data Scientist [Austin, TX]
