) KDnuggets™ News 18:n18, May 2: Blockchain Explained in 7 Python Functions; Data Science Dirty Secret; Choosing the Right Evaluation Metric
Tags: Blockchain, Convolutional Neural Networks, Data Science, Machine Learning, Metrics, numpy, Python
Also: Building Convolutional Neural Network using NumPy from Scratch; Data Science Interview Guide; Implementing Deep Learning Methods and Feature Engineering for Text Data: The GloVe Model; Jupyter Notebook for Beginners: A Tutorial
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Blockchain Explained in 7 Python Functions
- Choosing the Right Metric for Evaluating Machine Learning Models - Part 1
- The Dirty Little Secret Every Data Scientist Knows (but won't admit)
- Machine Learning Engineer, Researcher, Data Scientist have the highest job satisfaction
Building Convolutional Neural Network using NumPy from Scratch
- Data Science Interview Guide
- Implementing Deep Learning Methods and Feature Engineering for Text Data: The GloVe Model
Tutorials, Overviews
- Jupyter Notebook for Beginners: A Tutorial
- 50+ Useful Machine Learning & Prediction APIs, 2018 Edition
- Data Science vs Machine Learning vs Data Analytics vs Business Analytics
- Implementing Deep Learning Methods and Feature Engineering for Text Data: FastText
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- Operational Machine Learning: Seven Considerations for Successful MLOps
- How to Make AI More Accessible
- What should be focus areas for Machine Learning / AI in 2018?
- Doing Real-Time Data Analysis With Db2 Event Store
- Bitcoin Trade Signals
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- Actionable Insights with Predictive Analytics for Marketers, May 9
- Modernize your data infrastructure with Looker + AWS
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- Train AI 2018: Garry Kasparov, Andrej Karpathy keynotes and the best in AI
- Hear the latest AI advancements in robotics & automation from Uber, Hitachi, Google & more
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- Top Stories, Apr 23-29: Blockchain Explained in 7 Python Functions; Building Convolutional Neural Network using NumPy from Scratch
- Top KDnuggets tweets, Apr 18-24: Top 20 Python #AI and #MachineLearning Open Source Projects; 7 Books to Grasp Mathematical Foundations of #DataScience
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From Data Science Interview Guide
