ArtificialIntelligenceArticles
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for who have a passion for -
1. #ArtificialIntelligence
2. Machine Learning
3. Deep Learning
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Interview with The Youngest Kaggle Grandmaster: Mikel Bober-Irizar (anokas)

https://hackernoon.com/interview-with-the-youngest-kaggle-grandmaster-mikel-bober-irizar-anokas-17dfd2461070
Access free GPU compute via Colab

https://colab.research.google.com/notebooks/welcome.ipynb

Colaboratory is a research tool for machine learning education and research. It’s a Jupyter notebook environment that requires no setup to use.

@ArtificialIntelligenceArticles
Deep learning in radiology: an overview of the concepts and a survey of the state of the art
https://arxiv.org/abs/1802.08717
How to implement a YOLO (v3) object detector from scratch in PyTorch: Part 1

Blog by Ayoosh Kathuria: https://blog.paperspace.com/how-to-implement-a-yolo-object-detector-in-pytorch/?mlreview
"Deep Reinforcement Learning with Subgoals"#NIPS 2017
Invited talk by DeepMind’s Professor David Silver
https://vimeo.com/249557775 @ArtificialIntelligenceArticles
Practical Text Classification With Python and Keras

By Nikolai Janakiev: https://realpython.com/python-keras-text-classification/
Introduction to Applied Linear Algebra – Vectors, Matrices, and Least Squares

By Stephen Boyd and Lieven Vandenberghe, Cambridge University https://web.stanford.edu/~boyd/vmls/
Complex-YOLO: Real-time 3D Object Detection on Point Clouds

Simon et al.: https://arxiv.org/abs/1803.06199
pair2vec: Compositional Word-Pair Embeddings for Cross-Sentence Inference

Joshi et al.: https://arxiv.org/abs/1810.08854
SURREAL: Open-Source Reinforcement Learning Framework and Robot Manipulation Benchmark

https://surreal.stanford.edu/
BabyAI: First Steps Towards Grounded Language Learning With a Human In the Loop"

Maxime Chevalier-Boisvert et al.: https://arxiv.org/abs/1810.08272
NEP 18 — A dispatch mechanism for NumPy’s high level array functions

Abstact: "We propose the array_function protocol, to allow arguments of NumPy functions to define how that function operates on them. This will allow using NumPy as a high level API for efficient multi-dimensional array operations, even with array implementations that differ greatly from numpy.ndarray."

https://www.numpy.org/neps/nep-0018-array-function-protocol.html
#numpy
These enhancements enable us to process large 3D dark matter distribution and predict the cosmological parameters ΩM, σ8, and ns with unprecedented accuracy arxiv.org/abs/1808.04728