KDnuggets 16:n37: Top Data Science Videos; 12 Interesting Big Data Careers; Deep Learning Key Terms
Gregory Piatetsky-Shapiro
Part-time philosopher, Retired, Data Scientist, KDD and KDnuggets Founder, was LinkedIn Top Voice on Data Science & Analytics. Currently helping Ukrainian refugees in MA.
Features
- Top 10 Data Science Videos on Youtube
- Top 12 Interesting Careers to Explore in Big Data
- Deep Learning Key Terms, Explained
- Artificial Intelligence, Deep Learning, and Neural Networks, Explained
- MLDB: The Machine Learning Database
- PAW Business, NYC Oct 23-27: Last Chance to Save
Software
- Data Science + Criminal Justice
- Deep Learning meets Deep Deployment
- The R Graph Gallery Data Visualization Collection
Tutorials, Overviews, How-Tos
Opinions
- European Machine Intelligence Landscape
- Strata Hadoop 2016: Fast Data and Robots
- EDISON Data Science Framework to define the Data Science Profession
- How to Get Stuff Done at a Data Startup
- CAP Certification Program: What's on the Exam?
Interviews
- Data Preparation Tips, Tricks, and Tools: An Interview with the Insiders
- LinkedIn Knowledge Graph - KDnuggets Interview
Reports
News
Novel Tensor Mining Tool to Enable Automated Modeling
Courses
- Regis University MS in Data Science Now Offered On Campus
- NYU Stern - Master of Science in Business Analytics
- K2 Data Science Bootcamp
Meetings
- PAW Business, NYC Oct 23-27: Last Chance to Save
- Apache: Big Data Europe (Nov. 14-16) - Leading Event for Big Data Technologists
Jobs
- Intellectual Ventures: Sr. Machine Learning Algorithm Development Software Engineer
- Equifax: Strategic Data Performance Analyst
- Equifax: Senior Statistical Modeler
- Equifax: Senior Director, Search-Match & Data-Linking
- Equifax: Metadata Expert
- Equifax: Employee Analytics Leader
- Equifax: Data Visualization Engineer
- Equifax: Data Strategy Leader
- Zaireo: Data Scientist
- Zynga: Principal Data Scientist
- Predictive Science: Data Scientist
Top Tweets
PhD in Computer Science, Data Scientist
8 年Parece-me um bocadinho simplista e até enviesado... (mas, qual a area de data science que n?o sofre do enviesamento dos seus algoritmos!)