Issue #20
October 13, 2019
- 1. The State of Machine Learning Frameworks in 2019 [thegradient.pub]
- 2. Predicting bank distress in the UK with machine learning [bankofengland.co.uk]
- 3. 20 Python Snippets You Should Learn Today [medium.com/better-programming]
- 4. The Economics of Data [imf.org]
- 5. The current state of AI and Deep Learning: A reply to Yoshua Bengio [medium.com/wwblog]
- 6. Why deep-learning AIs are so easy to fool [nature.com]
- 7. How I overcame impostor syndrome after leaving academia [nature.com]
- • Quantifying the future lethality of terror organizations (Y. Yang, A. R. Pah, B. Uzzi)
- • Generalizing the inverse FFT off the unit circle (V. Sukhoy, A. Stoytchev)
- • A Selective Overview of Deep Learning (J. Fan, C. Ma, Y. Zhong)
- • Can We Distinguish Machine Learning from Human Learning? (V. Bier, P. B. Kantor, G. Lupyan, X. Zhu)
- • Overton: A Data System for Monitoring and Improving Machine-Learned Products (C. Ré, F. Niu, P. Gudipati, C. Srisuwananukorn)
- • Green AI (R. Schwartz, J. Dodge, N. A. Smith, O. Etzioni)
- • 150 successful Machine Learning models: 6 lessons learned at Booking.com (P. Estevez, T. Mavridis, L. Bernardi)
Basic Stock data Manipulation - Python Programming for Finance p.3
All our videos are also available in our YouTube playlist.
Enjoy the newsletter?
Forward it to a friend, or subscribe to get it straight to your inbox.
Subscribe Free