Issue #62
August 2, 2020
- 1. Let's build a Full-Text Search engine [artem.krylysov.com]
- 2. Generative Adversarial Networks: Build Your First Models [realpython.com]
- 3. How to derive convolution from first principles [medium.com/@michael.bronstein]
- 4. Deep Learning's Most Important Ideas - A Brief Historical Review [dennybritz.com]
- 5. Are we in an AI overhang? [lesswrong.com]
- 6. Must-read papers on GNN [github.com/thunlp]
- 7. Large scale experimentation [multithreaded.stitchfix.com]
- 8. Darts: Time Series Made Easy in Python [medium.com/unit8-machine-learning-publication]
- • Epidemics as an adaptive driving force determining lifespan setpoints (P. V. Lidsky, R. Andino)
- • Interdependence and the cost of uncoordinated responses to COVID-19 (D. Holtz, M. Zhao, S. G. Benzell, C. Y. Cao, M. A. Rahimian, J. Yang, J. Allen, A. Collis, A. Moehring, T. Sowrirajan, D. Ghosh, Y. Zhang, P. S. Dhillon, C. Nicolaides, D. Eckles, S. Aral)
- • Mapping socioeconomic indicators using social media advertising data (M. Fatehkia, I. Tingzon, A. Orden, S. Sy, V. Sekara, M. Garcia-Herranz, I. Weber)
- • metric-learn: Metric Learning Algorithms in Python (W. de Vazelhes, C. J. Carey, Y. Tang, N. Vauquier, A. Bellet)
- • AI Explainability 360: An Extensible Toolkit for Understanding Data and Machine Learning Models (V. Arya, R. K. E. Bellamy, P.-Y. Chen, A. Dhurandhar, M. Hind, S. C. Hoffman, S. Houde, Q. V. Liao, R. Luss, A. Mojsilović, S. Mourad, P. Pedemonte, R. Raghavendra, J. T. Richards, P. Sattigeri, K. Shanmugam, M. Singh, K. R. Varshney, D. Wei, Y. Zhang)
- • On the unreasonable effectiveness of CNNs (A. Hauptmann, J. Adler)
- • The Representation Theory of Neural Networks (M. A. Armenta, P.-M. Jodoin)
Robert Meyer - Analysing user comments with Doc2Vec and Machine Learning classification
All our videos are also available in our YouTube playlist.
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