KDnuggets™ News 17:n45, Nov 29: New Poll: Data Science Methods Used? Deep Learning Specialization: 21 Lessons Learned
Also The 10 Statistical Techniques Data Scientists Need to Master; Did Spark Really Kill Hadoop? A Framework for Textual Data Science.
Features | Software | Tutorials | Opinions | Tops | News | Webcasts | Courses | Meetings | Jobs | Academic | Image of the week
Features
Software
Tutorials, Overviews
Opinions
Top Stories, Tweets
News
Webcasts and Webinars
Courses, Education
Meetings
Jobs
Academic
Image of the week
Features
- New Poll: Which Data Science / Machine Learning methods and tools you used?
Deep Learning Specialization by Andrew Ng - 21 Lessons Learned
- The 10 Statistical Techniques Data Scientists Need to Master
- Did Spark Really Kill Hadoop?
- A Framework for Approaching Textual Data Science Tasks
- Automated Feature Engineering for Time Series Data
- Best Masters in Data Science and Analytics in US/Canada
- Cartoon: Thanksgiving, Big Data, & Turkey Data Science.
Deep Learning Specialization by Andrew Ng - 21 Lessons Learned
A Framework for Approaching Textual Data Science TasksSoftware
- Natural Language Processing Library for Apache Spark - free to use
- The Python Graph Gallery
- PySpark SQL Cheat Sheet: Big Data in Python
- NVIDIA DGX Systems - Deep Learning Software Whitepaper
Tutorials, Overviews
- How To Unit Test Machine Learning Code
- Analyzing the Migration of Scientific Researchers
- How (and Why) to Create a Good Validation Set
- Understanding Objective Functions in Neural Networks
- Building a Wikipedia Text Corpus for Natural Language Processing
- Estimating an Optimal Learning Rate For a Deep Neural Network
- Generative Adversarial Networks - Part II
- Top 10 Videos on Deep Learning in Python
- 8 Ways to Improve Your Data Science Skills in 2 Years
- Capsule Networks Are Shaking up AI - Here's How to Use Them
- Basic Concepts of Feature Selection
Opinions
- Survival Analysis for Business Analytics
- Are Scientists Doing Too Much Research?
- Using TensorFlow for Predictive Analytics with Linear Regression
- Key Takeaways from Open Data Science Conference (ODSC) West 2017
- How (& Why) Data Scientists and Data Engineers Should Share a Platform
- Stop Doing Fragile Research
- You have created your first Linear Regression Model. Have you validated the assumptions?
Top Stories, Tweets
- Top Stories, Nov 20-26: Deep Learning Specialization by Andrew Ng - 21 Lessons Learned; A Framework for Approaching Textual Data Science Tasks
- Top Stories, Nov 13-19: The 10 Statistical Techniques Data Scientists Need to Master; Best Online Masters in Data Science and Analytics - a comprehensive, unbiased survey
- Top KDnuggets tweets, Nov 15-21: DeepLearning is "shallow": here are underlying concepts you need
- Top KDnuggets tweets, Nov 08-14: Approaching (Almost) Any NLP Problem on #Kaggle; Choosing an Open Source #MachineLearning Library
News
- [eBook] A Gentle Introduction to Apache Spark(tm)
- Call for Bids to Host KDD-202x
- DataScience.com Adds Former U.S. Chief Data Scientist DJ Patil to Advisory Board
Webcasts and Webinars
- Webinar: Data Preparation Essentials for Automated Machine Learning, Nov 29
- Taming the Python Visualization Jungle, Nov 29 Webinar
- Multichannel Marketing Attribution with Automated Machine Learning, Dec 12 Webinar
- Fusing Human and Machine for Seamless, Automated Insurance Claims (Webinar, Dec 14)
Courses, Education
- Implementing Enterprise AI course using TensorFlow and Keras
- A Course in Semantic Technologies for Designing a Proof-of-Concept, starting Nov 30
Meetings
- Chief Data & Analytics Officer Sydney, Mar 20-22, KDnuggets Offer
- We Speak Data at TDWI Las Vegas, Feb 11-16. Save w. code KD30 thru Dec 15
- Deep Learning in Robotics and Healthcare Summits: Join & save with KDnuggets offer
Jobs
- The Humanalysts: Data Analytics Team, 9
- Apple: Machine Learning-Industrial Methods Engineer
- American Family Insurance: Director, Data Science & Analytics
- HelloFresh: Machine Learning Engineer
- HelloFresh: Big Data Engineer
- HelloFresh: Senior Data Scientist
Academic
- USF Data Institute: Postdoc
- Virginia Tech: Assistant Professors in Data Analytics
- IESEG School of Management: Assistant, Associate or Full Professor in Marketing Analytics
Image of the week
