Review of materials on machine learning (February 13 - 20, 2017)

I present to your attention a selection of materials on machine learning and data analysis for the past week, which seemed interesting to me.

Events of the week

one. Deep Learning: Now and Future of Robotics. Skolkovo-Skoltech-NVIDIA workshop . February 21st.
2 Data Science Case Club . February 21st.
3 Data science breakfast . February 22.
four. Machine learning training . 25 February.

Training courses, conferences
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one. Online course "Introduction to the processing of natural language" from mid-March at stepik . Page last year .
2 Restart of the course “Neural Networks for Machine Learning” G. Hinton .
3 Video from the TensorFlow Developer Summit conference.
four. Video from the DataFest conference. Part 1 . Part 2 . Part 3 Part 4
five. Seminar Practical Machine Learning from Yandex (video). Subject: chat bots. Record November, but recently caught.

6 Open Data Day in Moscow .
7 Selection of materials on ML and DM .
eight. The Best Intro to Data Science Courses - Class Central Career Guides .
9. Published reports ICLR 2017 , which will be held in April this year in France.
ten. Oxford Deep NLP 2017 course .
UPD IliaSafonov
eleven. Conference in Yandex "Machine learning for business . "
12. Kaggle launched Google Cloud & YouTube-8M Video Understanding Challenge .
UPD jjdeluxe
13. Modern architectures of dialogue systems - Anatoly Vostryakov, Segmento. Video.

news

one. TensorFlow 1.0 comes out
2 Google has released a debugger for TensorFlow tfdbg
3 Weekly Digest from DataScienceCentral
4. Weekly review of the HighScalability portal .

Scientific articles, practical implementations, datasets

one. Time Series Forecast Case Study with Python: Monthly Armed Robberies in Boston .
2 Shopping datasets . Belgium retail market dataset (donated by Tom Brijs): it contains the retail market basket.
3 Hybrid Code Networks: practical and efficient end-to-end dialog control with supervised and reinforced learning .
four. Neural networks for beginners . Part 2.
five. Spectral Clustering via Graph Filtering: Consistency on the High-Dimensional Stochastic Block Model .
6 Performance of Distributed Deep Learning using ChainerMN .
7 Model Mis-specification and Inverse Reinforcement Learning .
eight. PyTorch Implementation: seq2seq Translation .
9. Automatically Segmenting Data With Clustering .
ten. Offline bilingual word vectors, orthogonal transformations and the inverted softmax .
eleven. Parallel Long Short-Term Memory for Multi-stream Classification .
12. Classification dataset, which recently published Quora.
13. Analyzing Six Deep Learning Tools for the Music Generation - The Asimov Institute .
14. HistWords: Word Embeddings for Historical Text .
15. The Data Stack . PDF, which contains all the tools for data analysis.
sixteen. Data Coding 101 - Introduction to Bash .
17 Time Series Forecast Case Study with Python: Annual Water Usage in Baltimore .
18. Gaussian-Dirichlet Posterior Dominance in Sequential Learning .
nineteen. Implementation of the InceptionV3 convolutional neural network using the Keras framework.
20. Understanding Deep Learning Models in NLP .
21. Web Scraping for Dataset Curation .
22 Software Engineering vs Machine Learning Concepts .
23. Frustratingly Short Attention Spans in Neural Language Modeling .
24 The robot interlocutor on the basis of a neural network .
25 Attacking machine learning with adversarial examples .
26 Introduction to Anomaly Detection .
27. 'AI brain scans' reveal what happens inside machine learning .
28 Open Sourcing TensorFlowOnSpark: Distributed Deep Learning on Big-Data Clusters .
29. Using NLP to understand the Super Bowl 51 ads battle .
thirty. Reading Files - 3D Convolutional Neural Network . Video.
31. Getting Started with Deep Learning .
32. Time Series Forecast Study with Python: Monthly Sales of French Champagne .