KDnuggets™ News 19:n36, Sep 25: The Hidden Risk of AI and Big Data; The 5 Sampling Algorithms every Data Scientist needs to know
Learn about unexpected risk of AI applied to Big Data; Study 5 Sampling Algorithms every Data Scientist needs to know; Read how one data scientist copes with his boring days of deploying machine learning; 5 beginner-friendly steps to learn ML with Python; and more.
- The Hidden Risk of AI and Big Data
- The 5 Sampling Algorithms every Data Scientist need to know
- Data Science is Boring (Part 1)
- Scikit-Learn & More for Synthetic Dataset Generation for Machine Learning
- 5 Beginner Friendly Steps to Learn Machine Learning and Data Science with Python
- Automatic Version Control for Data Scientists
- A 2019 Guide for Automatic Speech Recognition
- A Single Function to Streamline Image Classification with Keras
- Introducing IceCAPS: Microsoft's Framework for Advanced Conversation Modeling
- A Gentle Introduction to PyTorch 1.2
- Automate Hyperparameter Tuning for Your Models
- Applying Data Science to Cybersecurity Network Attacks & Events
- Reddit Post Classification
- Data Quality Assessment Is Not All Roses. What Challenges Should You Be Aware Of?
- 5 Famous Deep Learning Courses/Schools of 2019
- 12 Deep Learning Researchers and Leaders
Top Stories, Tweets
- Top Stories, Sep 16-22: Which Data Science Skills are core and which are hot/emerging ones?
- Top KDnuggets tweets, Sep 11-17: Python Libraries for Interpretable Machine Learning
- Beyond Explainability: A Practical Guide to Managing Risks in Machine Learning Models
- Python 2 End of Life Survey - Are You Prepared?
Webcasts and Webinars
- Getting to the Future First: How Social Data is Transforming Trend Discovery
- Webinar: Data-Driven Approaches to Forecasting
- See our recent jobs in AI, Analytics, Data Science, Machine Learning
- You can post a free short entry on KDnuggets jobs page for an industry or academic job related to AI, Big Data, Data Science, or Machine Learning, email - see details at kdnuggets.com/jobs
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