CytokitMicroscopy Image Cytometry Toolkit
Stars: ✭ 84 (-99.13%)
Deeplearning2020course materials for introduction to deep learning 2020
Stars: ✭ 90 (-99.07%)
Learning pythonSource material for Python Like You Mean it
Stars: ✭ 78 (-99.19%)
Airflow projectscaffold of Apache Airflow executing Docker containers
Stars: ✭ 84 (-99.13%)
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 (-99.09%)
Tensor LearningPython codes for low-rank tensor factorization, tensor completion, and tensor regression techniques.
Stars: ✭ 83 (-99.14%)
Covid19 DashboardA site that displays up to date COVID-19 stats, powered by fastpages.
Stars: ✭ 1,212 (-87.49%)
Fast ScnnImplementation of Fast-SCNN using Tensorflow 2.0
Stars: ✭ 91 (-99.06%)
Azure SentinelCloud-native SIEM for intelligent security analytics for your entire enterprise.
Stars: ✭ 1,208 (-87.53%)
Spark Nlp ModelsModels and Pipelines for the Spark NLP library
Stars: ✭ 88 (-99.09%)
Covid19 DataCOVID-19 workflows and datasets.
Stars: ✭ 84 (-99.13%)
PysheafPython Cellular Sheaf Library
Stars: ✭ 89 (-99.08%)
FoxtrackerFacial Head Pose Tracker for Gaming
Stars: ✭ 78 (-99.19%)
MlMachine learning projects, often on audio datasets
Stars: ✭ 83 (-99.14%)
TweetevalRepository for TweetEval
Stars: ✭ 78 (-99.19%)
Nosebooka nose plugin for finding and running IPython notebooks as nose tests
Stars: ✭ 77 (-99.21%)
Convergent learningCode for paper "Convergent Learning: Do different neural networks learn the same representations?"
Stars: ✭ 77 (-99.21%)
GancsCompressed Sensing MRI based on Deep Generative Adversarial Network
Stars: ✭ 83 (-99.14%)
Reinforcement LearningReinforcement learning material, code and exercises for Udacity Nanodegree programs.
Stars: ✭ 77 (-99.21%)
PsketchModular multitask reinforcement learning with policy sketches
Stars: ✭ 89 (-99.08%)
Machine Learning Without Any LibrariesThis is a collection of some of the important machine learning algorithms which are implemented with out using any libraries. Libraries such as numpy and pandas are used to improve computational complexity of algorithms
Stars: ✭ 77 (-99.21%)
LogomakerSoftware for the visualization of sequence-function relationships
Stars: ✭ 83 (-99.14%)
Coreml TrainingSource code for my blog post series "On-device training with Core ML"
Stars: ✭ 77 (-99.21%)
Game Theory And PythonGame Theory and Python, a workshop investigating repeated games using the prisoner's dilemma
Stars: ✭ 87 (-99.1%)
Object CxrAutomatic detection of foreign objects on chest X-rays
Stars: ✭ 77 (-99.21%)
Deepembeding图像检索和向量搜索,similarity learning,compare deep metric and deep-hashing applying in image retrieval
Stars: ✭ 83 (-99.14%)
Intro To SklearnNotebooks covering introductory material to ML, ML with sklearn and tips.
Stars: ✭ 76 (-99.22%)
Deeper Traffic Lights[repo not maintained] Check out https://diffgram.com if you want to build a visual intelligence
Stars: ✭ 89 (-99.08%)
Mlcourse生命情報の機械学習入門(新学術領域「先進ゲノム支援」中級講習会資料)
Stars: ✭ 83 (-99.14%)
H2o TutorialsTutorials and training material for the H2O Machine Learning Platform
Stars: ✭ 1,305 (-86.53%)
CoursesPython courses for the scientific researcher
Stars: ✭ 90 (-99.07%)
BerkeleyThe Hacker Within at the University of California - Berkeley
Stars: ✭ 88 (-99.09%)
GemfieldGemfield homework or libgemfield.so
Stars: ✭ 84 (-99.13%)