A Digest of Top 35+ Research Papers on Statistics. #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #JavaScript #ReactJS #GoLang #Serverless #DataScientist #Linux #Statistics
https://www.tandfonline.com/doi/full/10.1080/00031305.2019.1583913
https://www.tandfonline.com/doi/full/10.1080/00031305.2019.1583913
Taylor & Francis
Moving to a World Beyond “p < 0.05”
EDITORIAL: The editorial was written by the three editors acting as individuals and reflects their scientific views not an endorsed position of the American Statistical Association.
Machine Learning From Scratch
Bare bones #Python implementations of #MachineLearning models and algorithms with a focus on accessibility.
By Erik Linder-Noren: https://github.com/eriklindernoren/ML-From-Scratch...
See More
Bare bones #Python implementations of #MachineLearning models and algorithms with a focus on accessibility.
By Erik Linder-Noren: https://github.com/eriklindernoren/ML-From-Scratch...
See More
GitHub
GitHub - eriklindernoren/ML-From-Scratch: Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models…
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep lear...
Flowpoints
An intuitive approach to creating deep learning models
By Marius Brataas: https://github.com/mariusbrataas/flowpoints_ml#readme
#deeplearning #pytorch #machinelearning #python
An intuitive approach to creating deep learning models
By Marius Brataas: https://github.com/mariusbrataas/flowpoints_ml#readme
#deeplearning #pytorch #machinelearning #python
GitHub
mariusbrataas/flowpoints_ml
An intuitive approach to creating deep learning models - mariusbrataas/flowpoints_ml
ArviZ: Exploratory analysis of Bayesian models
Includes functions for posterior analysis, sample diagnostics, model checking, and comparison: https://arviz-devs.github.io/arviz/
#ArtificialIntelligence #Bayesian #BayesianInference #MachineLearning #Python
Includes functions for posterior analysis, sample diagnostics, model checking, and comparison: https://arviz-devs.github.io/arviz/
#ArtificialIntelligence #Bayesian #BayesianInference #MachineLearning #Python
ArviZ: Exploratory analysis of Bayesian models
Includes functions for posterior analysis, sample diagnostics, model checking, and comparison: https://arviz-devs.github.io/arviz/
#ArtificialIntelligence #Bayesian #BayesianInference #MachineLearning #Python
Includes functions for posterior analysis, sample diagnostics, model checking, and comparison: https://arviz-devs.github.io/arviz/
#ArtificialIntelligence #Bayesian #BayesianInference #MachineLearning #Python
MRI Images Created by #AI Could Help Train #DeepLearning Models. https://healthitanalytics.com/news/mri-images-created-by-ai-could-help-train-deep-learning-models #BigData #Analytics #MachineLearning #DataScience #IoT #IIoT #Python #RStats #TensorFlow #JavaScript #ReactJS #VueJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #NeuroScience
Uber’s EvoGrad is a dev library for evolutionary algorithms
Blog by Kyle Wiggers: https://venturebeat.com/2019/07/22/ubers-evograd-is-a-dev-library-for-evolutionary-algorithms/
#EvolutionaryAlgorithms #NaturalEvolutionStrategies #Python
Blog by Kyle Wiggers: https://venturebeat.com/2019/07/22/ubers-evograd-is-a-dev-library-for-evolutionary-algorithms/
#EvolutionaryAlgorithms #NaturalEvolutionStrategies #Python
VentureBeat
Uber’s EvoGrad is a dev library for evolutionary algorithms
Uber's EvoGrad is a development library for evolutionary machine learning algorithms. It's freely available on GitHub.
PracticalAI
A practical approach to learning machine learning
GitHub : https://github.com/GokuMohandas/practicalAI
- 📚 Notebooks on topics from basic Python to advanced deep learning techniques w/ #PyTorch
- 🖥️ Run everything using #Colab : https://colab.research.google.com/github/GokuMohandas/practicalAI/
#deeplearning #python #machinelearning #reinforcementlearning
A practical approach to learning machine learning
GitHub : https://github.com/GokuMohandas/practicalAI
- 📚 Notebooks on topics from basic Python to advanced deep learning techniques w/ #PyTorch
- 🖥️ Run everything using #Colab : https://colab.research.google.com/github/GokuMohandas/practicalAI/
#deeplearning #python #machinelearning #reinforcementlearning
Even young children when they look at a picture, not only identify objects such as "cat," "book," "chair." but also narrate the context and probably caption them. Now, computers are getting smart enough to do that too. In this TED talk, computer vision expert Fei-Fei Li describes the state of the art — including the database of 15 million photos her team built to "teach" a computer to understand pictures — and the key insights yet to come.#alintelligence #deeplearning #datascience #machinelearning #ML #Algorithm #Python #R #professional #industry #bigdata #ai #community #workforce
https://www.youtube.com/watch?v=40riCqvRoMs
https://www.youtube.com/watch?v=40riCqvRoMs
YouTube
How we teach computers to understand pictures | Fei Fei Li
When a very young child looks at a picture, she can identify simple elements: "cat," "book," "chair." Now, computers are getting smart enough to do that too. What's next? In a thrilling talk, computer vision expert Fei-Fei Li describes the state of the art…
Amazing work on generative adversarial networks by Tero Karras, Samuli Laine and Timo Aila of NVIDIA. The new architecture leads to an automatically learned, unsupervised separation of high-level attributes (e.g., pose and identity when trained on human faces) and stochastic variation in the generated images (e.g., freckles, hair), and it enables intuitive, scale-specific control of the synthesis. The new generator improves the state-of-the-art in terms of traditional distribution quality metrics, leads to demonstrably better interpolation properties, and also better disentangles the latent factors of variation. #education #professionals #careers #artificialintelligence #deeplearning #datascience #machinelearning #ML #Algorithm #Python #R #professional #industry #bigdata #ai #community #workforce
The research paper is available : http://stylegan.xyz/paper
Video link : https://www.youtube.com/watch?v=kSLJriaOumA
The research paper is available : http://stylegan.xyz/paper
Video link : https://www.youtube.com/watch?v=kSLJriaOumA
Neural Network Distiller: A Python Package For DNN Compression Research
Zmora et al.: https://arxiv.org/abs/1910.12232
#DeepLearning #MachineLearning #Python
Zmora et al.: https://arxiv.org/abs/1910.12232
#DeepLearning #MachineLearning #Python
arXiv.org
Neural Network Distiller: A Python Package For DNN Compression Research
This paper presents the philosophy, design and feature-set of Neural Network
Distiller, an open-source Python package for DNN compression research.
Distiller is a library of DNN compression...
Distiller, an open-source Python package for DNN compression research.
Distiller is a library of DNN compression...
PyRoboLearn: A Python Framework for Robot Learning Practitioners
Delhaisse et al.: https://robotlearn.github.io/pyrobolearn/
#ArtificialIntelligence #Python #Robotics
Delhaisse et al.: https://robotlearn.github.io/pyrobolearn/
#ArtificialIntelligence #Python #Robotics
This is an exhaustive list of Monte Carlo tree search papers from major conferences including NIPS, ICML, and AAAI. Some of them with publicly available implementations.
https://github.com/benedekrozemberczki/awesome-monte-carlo-tree-search-papers
#datascience #machinelearning #deeplearning #python #ai #analytics #datamining
https://github.com/benedekrozemberczki/awesome-monte-carlo-tree-search-papers
#datascience #machinelearning #deeplearning #python #ai #analytics #datamining
GitHub
GitHub - benedekrozemberczki/awesome-monte-carlo-tree-search-papers: A curated list of Monte Carlo tree search papers with implementations.
A curated list of Monte Carlo tree search papers with implementations. - GitHub - benedekrozemberczki/awesome-monte-carlo-tree-search-papers: A curated list of Monte Carlo tree search papers with ...