Dat8General Assembly's 2015 Data Science course in Washington, DC
Stars: ✭ 1,516 (+367.9%)
50 Days Of MlA day to day plan for this challenge (50 Days of Machine Learning) . Covers both theoretical and practical aspects
Stars: ✭ 218 (-32.72%)
Ds and ml projectsData Science & Machine Learning projects and tutorials in python from beginner to advanced level.
Stars: ✭ 56 (-82.72%)
Pymc Example ProjectExample PyMC3 project for performing Bayesian data analysis using a probabilistic programming approach to machine learning.
Stars: ✭ 90 (-72.22%)
Machine Learning With PythonPractice and tutorial-style notebooks covering wide variety of machine learning techniques
Stars: ✭ 2,197 (+578.09%)
EpisodesSelf Hosted TV show Episode tracker and recommender built using django, bootstrap4.
Stars: ✭ 160 (-50.62%)
dstoolboxTools that make working with scikit-learn and pandas easier.
Stars: ✭ 43 (-86.73%)
DS-Cookbook101A jupyter notebook having all most frequent used code snippet for daily data scienceoperations
Stars: ✭ 59 (-81.79%)
Django Rest Pandas📊📈 Serves up Pandas dataframes via the Django REST Framework for use in client-side (i.e. d3.js) visualizations and offline analysis (e.g. Excel)
Stars: ✭ 1,030 (+217.9%)
ImlКурс "Введение в машинное обучение" (ВМК, МГУ имени М.В. Ломоносова)
Stars: ✭ 46 (-85.8%)
DaskParallel computing with task scheduling
Stars: ✭ 9,309 (+2773.15%)
ZatZeek Analysis Tools (ZAT): Processing and analysis of Zeek network data with Pandas, scikit-learn, Kafka and Spark
Stars: ✭ 303 (-6.48%)
MarsMars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.
Stars: ✭ 2,308 (+612.35%)
30 Days Of PythonLearn Python for the next 30 (or so) Days.
Stars: ✭ 1,748 (+439.51%)
Artificial Intelligence Deep Learning Machine Learning TutorialsA comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Climate / Energy, Automotives, Retail, Pharma, Medicine, Healthcare, Policy, Ethics and more.
Stars: ✭ 2,966 (+815.43%)
PracticalMachineLearningA collection of ML related stuff including notebooks, codes and a curated list of various useful resources such as books and softwares. Almost everything mentioned here is free (as speech not free food) or open-source.
Stars: ✭ 60 (-81.48%)
Arch-Data-ScienceArchlinux PKGBUILDs for Data Science, Machine Learning, Deep Learning, NLP and Computer Vision
Stars: ✭ 92 (-71.6%)
DataSciPyData Science with Python
Stars: ✭ 15 (-95.37%)
MachinelearningcourseA collection of notebooks of my Machine Learning class written in python 3
Stars: ✭ 35 (-89.2%)
SkootA package for data science practitioners. This library implements a number of helpful, common data transformations with a scikit-learn friendly interface in an effort to expedite the modeling process.
Stars: ✭ 50 (-84.57%)
Mlcourse.aiOpen Machine Learning Course
Stars: ✭ 7,963 (+2357.72%)
Docker Alpine Python MachinelearningSmall Docker image with Python Machine Learning tools (~180MB) https://hub.docker.com/r/frolvlad/alpine-python-machinelearning/
Stars: ✭ 76 (-76.54%)
StudybookStudy E-Book(ComputerVision DeepLearning MachineLearning Math NLP Python ReinforcementLearning)
Stars: ✭ 1,457 (+349.69%)
Practical Machine Learning With PythonMaster the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.
Stars: ✭ 1,868 (+476.54%)
PbpythonCode, Notebooks and Examples from Practical Business Python
Stars: ✭ 1,724 (+432.1%)
Pandas VideosJupyter notebook and datasets from the pandas Q&A video series
Stars: ✭ 1,716 (+429.63%)
CodeCompilation of R and Python programming codes on the Data Professor YouTube channel.
Stars: ✭ 287 (-11.42%)
Scikit Learn VideosJupyter notebooks from the scikit-learn video series
Stars: ✭ 3,254 (+904.32%)
LearnpythonforresearchThis repository provides everything you need to get started with Python for (social science) research.
Stars: ✭ 163 (-49.69%)
Trump LiesTutorial: Web scraping in Python with Beautiful Soup
Stars: ✭ 201 (-37.96%)
Python for mlbrief introduction to Python for machine learning
Stars: ✭ 29 (-91.05%)
Orange3🍊 📊 💡 Orange: Interactive data analysis
Stars: ✭ 3,152 (+872.84%)
ElandPython Client and Toolkit for DataFrames, Big Data, Machine Learning and ETL in Elasticsearch
Stars: ✭ 235 (-27.47%)
Jetson ContainersMachine Learning Containers for NVIDIA Jetson and JetPack-L4T
Stars: ✭ 223 (-31.17%)
datascienvdatascienv is package that helps you to setup your environment in single line of code with all dependency and it is also include pyforest that provide single line of import all required ml libraries
Stars: ✭ 53 (-83.64%)
online-course-recommendation-systemBuilt on data from Pluralsight's course API fetched results. Works with model trained with K-means unsupervised clustering algorithm.
Stars: ✭ 31 (-90.43%)
skippaSciKIt-learn Pipeline in PAndas
Stars: ✭ 33 (-89.81%)
A-Detector⭐ An anomaly-based intrusion detection system.
Stars: ✭ 69 (-78.7%)
AIPortfolioUse AI to generate a optimized stock portfolio
Stars: ✭ 28 (-91.36%)
machine-learning-capstone-projectThis is the final project for the Udacity Machine Learning Nanodegree: Predicting article retweets and likes based on the title using Machine Learning
Stars: ✭ 28 (-91.36%)
Crime AnalysisAssociation Rule Mining from Spatial Data for Crime Analysis
Stars: ✭ 20 (-93.83%)
PythondatasciencehandbookThe book was written and tested with Python 3.5, though other Python versions (including Python 2.7) should work in nearly all cases.
Stars: ✭ 31,995 (+9775%)
five-minute-midasPredicting Profitable Day Trading Positions using Decision Tree Classifiers. scikit-learn | Flask | SQLite3 | pandas | MLflow | Heroku | Streamlit
Stars: ✭ 41 (-87.35%)
Try Django 19Try Django 1.9 is an introduction to Django version 1.9 by creating a simple, yet robust, Django blog. This series covers a variety of Django basics as well as Django 1.9 specific material. Created by Team CFE @ http://joincfe.com.
Stars: ✭ 279 (-13.89%)
PyafPyAF is an Open Source Python library for Automatic Time Series Forecasting built on top of popular pydata modules.
Stars: ✭ 289 (-10.8%)