Good afternoon! This is the third digest of materials on machine learning and data analysis, which appeared after a long break.
The events of the upcoming week
1. Data science breakfast. April 25 from 9:30 to 12-00 in the Cafe-bakery “Paradise Pie, pr-t. Mira, 26, p. 1, Moskva
2. 5th DataFest. 28 April.
3. NeuroHive 2018. Open source online hackathon for developers of neural networks.
1. We break into 2018 with the next big release: release of version 11.3 of Wolfram Language and Mathematica.
2. TensorFlow 1.8.0-rc0.
3. Weekly review of the portal HighScalability.
4. Passing cs231n together (in Russian).
Scientific articles, practical implementations, data sets
1. Python module to easily generate text using a pretrained character-based recurrent neural network ..
2. Official taiga resistance 2.0.
3. Swift for TensorFlow simulation.
4. Text Classification with TensorFlow Estimators.
5. Convolutional Neural Networks for Relation Extraction
6. It’s Training Cats and Dogs: NVIDIA Research Uses AI to Turn Cats into Dogs, Lions and Tigers, Too.
7. Problems of image segmentation with the help of the neural network Unet.
8. Which of the Hollywood stars is most similar to my voice ?.
9. Neural Style Transfer: A Review.
10. Implementations of 15 NLP research papers using Keras, Tensorflow, and Scikit Learn ..
11. The 2018 Stanford CS224n NLP course projects are now online. A lot of them are pretty impressive ..
12. Collection of popular object detection models with pre-trained weights in TensorFlow.
13. Representing Language with Recurrent and Convolutional Layers: An Authorship Attribution Example.
14. Data Science Bowl 2018. Orisanie decision of the winner.
15. Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking
16. How to select characteristics and select hyperparameters by testing statistical hypotheses.
17. TwinGAN – Cross-Domain Translation of Human Portraits.
18. Shared Autonomy via Deep Reinforcement Learning.
19. Data Augmentation | How to use Deep Learning when you have Limited Data.
20. The fall of RNN / LSTM.
21. Another article on the recognition of workers without helmets by neural networks.
22. Speed up TensorFlow Inference on GPUs with TensorRT.
23. How Music Generated by Artificial Intelligence Is Reshaping – Not Destroying – The Industry.
24. Semantic Segmentation – U-Net (Part 1).
25. Association rules, or beer with diapers.
26. Understand how works Resnet … without talking about residual.
27. SfSNet: Learning Shape, Reflectance and Illuminance of Faces’ in the wild.
28. A List Of The Top 10 Deep Learning Papers, The 2018 Edition.
29. Yann LeCun: Power and Limits of Deep Learning for Signal Understanding (ICASSP 2018 plenary). Video.
30. Simple Tensorflow implementation of “Multimodal Unsupervised Image-to-Image Translation”.
31. SNcGAN – Generate Conditional Images.
32. Deploying Deep Learning Models on Kubernetes with GPUs.
33. Apply the Deep Watershed Transform in the Kaggle Data Science Bowl 2018 competition.
34. How to implement a YOLO (v3) object detector from scratch in PyTorch: Part 1, Part 2, Part 3, Part 4, Part 5.
35. A Keras implementation of YOLOv3 (Tensorflow backend) allanzelener/ YAD2K ..
36. Pytorch implementation of MaxPoolingLoss ..
37. An intuitive introduction to Generative Adversarial Networks (GANs).
38. Nice ideas about unit testing ML code.
39. What is asked for an interview on AI in Apple ?.
40. A collection of popular Data Science Competitions.
41. Monte-Carlo Search for Magic: The Gathering.
42. Dataset “The Open Semantics of the Russian Language.”
Previous issue: Overview of materials on machine learning.