ChecklistBeyond Accuracy: Behavioral Testing of NLP models with CheckList
Stars: ✭ 1,290 (+1333.33%)
Spotify Recsys ChallengeA complete set of Recommender Systems techniques used in the Spotify Recsys Challenge 2018 developed by a team of MSc students in Politecnico di Milano.
Stars: ✭ 89 (-1.11%)
Caps Stars: ✭ 89 (-1.11%)
Smiles TransformerOriginal implementation of the paper "SMILES Transformer: Pre-trained Molecular Fingerprint for Low Data Drug Discovery" by Shion Honda et al.
Stars: ✭ 86 (-4.44%)
LogohunterDeep learning tool to find brand logos in everyday pictures
Stars: ✭ 90 (+0%)
Machine Learning NumpyGathers Machine learning models using pure Numpy to cover feed-forward, RNN, CNN, clustering, MCMC, timeseries, tree-based, and so much more!
Stars: ✭ 90 (+0%)
BerkeleyThe Hacker Within at the University of California - Berkeley
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ReadingbricksA structured collection of tagged notes about machine learning theory and practice endowed with search infrastructure that allows users to read requested info only.
Stars: ✭ 90 (+0%)
Basketball analyticsRepository which contains various scripts and work with various basketball statistics
Stars: ✭ 88 (-2.22%)
Blog ResourcesThis repo will contain the resources available in my blog for learning
Stars: ✭ 89 (-1.11%)
Fairness In MlThis repository contains the full code for the "Towards fairness in machine learning with adversarial networks" blog post.
Stars: ✭ 88 (-2.22%)
MagnetMAGNet: Multi-agents control using Graph Neural Networks
Stars: ✭ 88 (-2.22%)
Stanford Project Predicting Stock Prices Using A Lstm NetworkStanford Project: Artificial Intelligence is changing virtually every aspect of our lives. Today’s algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is an exciting time to adopt a disruptive technology that will transform how everyone invests for generations. Models that explain the returns of individual stocks generally use company and stock characteristics, e.g., the market prices of financial instruments and companies’ accounting data. These characteristics can also be used to predict expected stock returns out-of-sample. Most studies use simple linear models to form these predictions [1] or [2]. An increasing body of academic literature documents that more sophisticated tools from the Machine Learning (ML) and Deep Learning (DL) repertoire, which allow for nonlinear predictor interactions, can improve the stock return forecasts [3], [4] or [5]. The main goal of this project is to investigate whether modern DL techniques can be utilized to more efficiently predict the movements of the stock market. Specifically, we train a LSTM neural network with time series price-volume data and compare its out-of-sample return predictability with the performance of a simple logistic regression (our baseline model).
Stars: ✭ 88 (-2.22%)
XpediteA non-sampling profiler purpose built to measure and optimize performance of ultra low latency/real time systems
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Pymc Example ProjectExample PyMC3 project for performing Bayesian data analysis using a probabilistic programming approach to machine learning.
Stars: ✭ 90 (+0%)
Quantum LearningThis repository contains the source code used to produce the results presented in the paper "Machine learning method for state preparation and gate synthesis on photonic quantum computers".
Stars: ✭ 89 (-1.11%)
Cc6205Natural Language Processing
Stars: ✭ 88 (-2.22%)
Deeplearning2020course materials for introduction to deep learning 2020
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Computer visionSome computer vision tutorials for my articles
Stars: ✭ 90 (+0%)
Py4fiPython for Finance (O'Reilly)
Stars: ✭ 1,288 (+1331.11%)
PysheafPython Cellular Sheaf Library
Stars: ✭ 89 (-1.11%)
Ipython NotebooksThis repository contains IPython notebooks that I have written.
Stars: ✭ 88 (-2.22%)
PsketchModular multitask reinforcement learning with policy sketches
Stars: ✭ 89 (-1.11%)
Wine Deep LearningExploring applications of deep learning to the world of wine
Stars: ✭ 88 (-2.22%)
Learning Notes💡 Repo of learning notes in DRL and DL, theory, codes, models and notes maybe.
Stars: ✭ 90 (+0%)
Deeper Traffic Lights[repo not maintained] Check out https://diffgram.com if you want to build a visual intelligence
Stars: ✭ 89 (-1.11%)
CrlImplementation of the paper "Cascade Residual Learning: A Two-stage Convolutional Neural Network for Stereo Matching"
Stars: ✭ 89 (-1.11%)
StnnCode for the paper "Spatio-Temporal Neural Networks for Space-Time Series Modeling and Relations Discovery"
Stars: ✭ 90 (+0%)
FashionnetFashion recommender system using deep learning
Stars: ✭ 90 (+0%)