Ten Simple Rules for Reproducible Research in Jupyter Notebooks
Rule et al.: https://arxiv.org/abs/1810.08055
#100DaysOfMLCode #BigData #ComputerScience #DataScience #MachineLearning
Rule et al.: https://arxiv.org/abs/1810.08055
#100DaysOfMLCode #BigData #ComputerScience #DataScience #MachineLearning
DIVE: Turn your data into stories without writing code
The publicly available system integrates semi-automated visualization and statistical analysis features. By the MIT Media Lab
https://dive.media.mit.edu
#ArtificialIntelligence #BigData #MachineLearning
@ArtificialIntelligenceArticles
The publicly available system integrates semi-automated visualization and statistical analysis features. By the MIT Media Lab
https://dive.media.mit.edu
#ArtificialIntelligence #BigData #MachineLearning
@ArtificialIntelligenceArticles
New research group at Oxford Comp Sci!
Oxford Applied and Theoretical Machine Learning Group (OATML): http://oatml.cs.ox.ac.uk/
#artificialintelligence #bigdata #machinelearning #neuralnetworks
Oxford Applied and Theoretical Machine Learning Group (OATML): http://oatml.cs.ox.ac.uk/
#artificialintelligence #bigdata #machinelearning #neuralnetworks
FishExplorer
1.5 million neurons, cell-level activity during multiple behaviors
15 TB raw, 56 GB compressed
18 fish whole-brain data, ~100k neurons/fish
Data and code: https://github.com/xiuyechen/fishexplorer
Paper:https://www.sciencedirect.com/science/article/pii/S0896627318308444
#bigdata #brain #datascience #machinelearning #research
1.5 million neurons, cell-level activity during multiple behaviors
15 TB raw, 56 GB compressed
18 fish whole-brain data, ~100k neurons/fish
Data and code: https://github.com/xiuyechen/fishexplorer
Paper:https://www.sciencedirect.com/science/article/pii/S0896627318308444
#bigdata #brain #datascience #machinelearning #research
GitHub
xiuyechen/FishExplorer
interactive analysis of calcium imaging data from larval zebrafish - xiuyechen/FishExplorer
Open Courses and Textbooks
By Samuel G. Finlayson: https://sgfin.github.io/learning-resources/
#artificialintelligence #bigdata #deeplearning #machinelearning #neuralnetworks
By Samuel G. Finlayson: https://sgfin.github.io/learning-resources/
#artificialintelligence #bigdata #deeplearning #machinelearning #neuralnetworks
The Physics of Brain Network Structure. #BigData #Analytics #DeepLearning https://arxiv.org/abs/1809.06441 @ArtificialIntelligenceArticles
SQuAD2.0: The Stanford Question Answering Dataset
Leaderboard: https://rajpurkar.github.io/SQuAD-explorer/
#artificialintelligence #bigdata #deeplearning #machinelearning #NaturalLanguageProcessing
Leaderboard: https://rajpurkar.github.io/SQuAD-explorer/
#artificialintelligence #bigdata #deeplearning #machinelearning #NaturalLanguageProcessing
Yes, We Can Now Construct Speech from Brain Waves. # #BigData #Analytics #DeepLearning #MachineLearning #DataScience #AI #IoT #IIoT #Python #RStats #TensorFlow #JavaScript #ReactJS #VueJS #GoLang #Serverless #DataScientist #Linux #NeuroScience
https://www.biorxiv.org/content/10.1101/350124v2
https://www.biorxiv.org/content/10.1101/350124v2
The Machines That Will Read Your Mind: https://www.wsj.com/articles/the-machines-that-will-read-your-mind-11554476156
#AI #BigData #DataScience #MachineLearning #Neuroscience #NeuralNetworks #DeepLearning
#AI #BigData #DataScience #MachineLearning #Neuroscience #NeuralNetworks #DeepLearning
Introducing SuperGLUE: A New Hope Against Muppetkind
Blog by Alex Wang: https://medium.com/@wang.alex.c/introducing-superglue-a-new-hope-against-muppetkind-2779fd9dcdd5
#MachineLearning #NLP #BigData
Blog by Alex Wang: https://medium.com/@wang.alex.c/introducing-superglue-a-new-hope-against-muppetkind-2779fd9dcdd5
#MachineLearning #NLP #BigData
Medium
Introducing SuperGLUE: A New Hope Against Muppetkind
Over the past year, a machine learning models have dramatically improved scores across many language understanding tasks in NLP. ELMo…
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.
How to deliver on Machine Learning projects
A guide to the ML Engineering Loop.
By Emmanuel Ameisen and Adam Coates: https://blog.insightdatascience.com/how-to-deliver-on-machine-learning-projects-c8d82ce642b0
#ArtificialIntelligence #BigData #DataScience #DeepLearning #MachineLearning
A guide to the ML Engineering Loop.
By Emmanuel Ameisen and Adam Coates: https://blog.insightdatascience.com/how-to-deliver-on-machine-learning-projects-c8d82ce642b0
#ArtificialIntelligence #BigData #DataScience #DeepLearning #MachineLearning
Medium
How to deliver on Machine Learning projects
A guide to the ML Engineering Loop
Five Functions of the Brain that are Inspiring #AI Research: https://towardsdatascience.com/five-functions-of-the-brain-that-are-inspiring-ai-research-2ba482ab8e2a
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#BigData #MachineLearning #DataScience #Neuroscience #NeuralNetworks #Algorithms #DeepLearning
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#BigData #MachineLearning #DataScience #Neuroscience #NeuralNetworks #Algorithms #DeepLearning
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
Five fundamental truths about algorithms for anyone living in the Digital Age. I would love to hear your thoughts! #machinelearning #bigdata #algorithms #artificialintelligence
https://www.youtube.com/watch?v=XYCq3K_XxZY&feature=share&fbclid=IwAR2CCOiLZgbNXG0AQC5hRfTNhETBlJ60ieQmVgXSYlXrwRHhugk_f01NSvg
https://www.youtube.com/watch?v=XYCq3K_XxZY&feature=share&fbclid=IwAR2CCOiLZgbNXG0AQC5hRfTNhETBlJ60ieQmVgXSYlXrwRHhugk_f01NSvg
YouTube
The power and perils of algorithms | Gah-Yi Ban | TEDxLondonBusinessSchool
Gah-Yi Ban's talk hopes to help us understand the role of algorithms in our present lives, and how we can shape their role in our future. Gah-Yi Ban is a pro...
WikiMatrix: Mining 135M Parallel Sentences in 1620 Language Pairs from Wikipedia
Schwenk et al.: https://arxiv.org/abs/1907.05791
Data: https://github.com/facebookresearch/LASER/tree/master/tasks/WikiMatrix
#artificialintelligence #bigdata #datascience #machinelearning
Schwenk et al.: https://arxiv.org/abs/1907.05791
Data: https://github.com/facebookresearch/LASER/tree/master/tasks/WikiMatrix
#artificialintelligence #bigdata #datascience #machinelearning
Ten quick tips for effective dimensionality reduction
Lan Huong Nguyen and Susan Holmes : https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1006907
#ArtificialIntelligence #BigData #DataScience
Lan Huong Nguyen and Susan Holmes : https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1006907
#ArtificialIntelligence #BigData #DataScience
journals.plos.org
Ten quick tips for effective dimensionality reduction
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
Machine Learning Unlocks Library of The Human Brain. #BigData #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #NeuroScience
http://thetartan.org/2019/11/11/scitech/brain-thoughts
http://thetartan.org/2019/11/11/scitech/brain-thoughts