1063 Open source projects that are alternatives of or similar to How-to-score-0.8134-in-Titanic-Kaggle-Challenge

A collection of notebooks of my Machine Learning class written in python 3

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

🛠 All-in-one web-based IDE specialized for machine learning and data science.

Practice and tutorial-style notebooks covering wide variety of machine learning techniques

Create HTML profiling reports from pandas DataFrame objects

📚 Various cheatsheets in PDF

Credit Card Fraud Detection using ML: IEEE style paper + Jupyter Notebook

A 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.

Computer vision sabbatical study materials

도서 "핸즈온 머신러닝"의 예제와 연습문제를 담은 주피터 노트북입니다.

Master 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.

Kaggle을 처음 접하는 사람들을 위한 문서

Top 5th percentile solution to the Kaggle knowledge problem - Bike Sharing Demand

Using Kaggle Data and Real World Data for Data Science and prediction in Python, R, Excel, Power BI, and Tableau.

In this work, we propose a deterministic version of Local Interpretable Model Agnostic Explanations (LIME) and the experimental results on three different medical datasets shows the superiority for Deterministic Local Interpretable Model-Agnostic Explanations (DLIME).

Kaggle Titanic example

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

Automated Machine Learning Pipeline with Feature Engineering and Hyper-Parameters Tuning 🚀

A python library for decision tree visualization and model interpretation.

PyAF is an Open Source Python library for Automatic Time Series Forecasting built on top of popular pydata modules.

Ways of doing Data Science Engineering and Machine Learning in R and Python

Association Rule Mining from Spatial Data for Crime Analysis

Python API for Intelligent Visual Data Discovery

Formed trajectories of sets of points.Experimented on finding similarities between trajectories based on DTW (Dynamic Time Warping) and LCSS (Longest Common SubSequence) algorithms.Modeled trajectories as strings based on a Grid representation.Benchmarked KNN, Random Forest, Logistic Regression classification algorithms to classify efficiently t…

A 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.

📊 All of courses, assignments, exercises, mini-projects and books that I've done so far in the process of learning by myself Machine Learning and Data Science.

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There are plenty of courses and tutorials that can help you learn machine learning from scratch but here in GitHub, I want to solve some Kaggle competitions as a comprehensive workflow with python packages. After reading, you can use this workflow to solve other real problems and use it as a template.

🍊 📊 💡 Orange: Interactive data analysis

exploratory data analysis using random forests

A Lightweight Decision Tree Framework supporting regular algorithms: ID3, C4,5, CART, CHAID and Regression Trees; some advanced techniques: Gradient Boosting (GBDT, GBRT, GBM), Random Forest and Adaboost w/categorical features support for Python

R on Apache Spark (SparkR) tutorials for Big Data analysis and Machine Learning as IPython / Jupyter notebooks

A python library to build Model Trees with Linear Models at the leaves.

Python for chemoinformatics

[UNMAINTAINED] Automated machine learning- just give it a data file! Check out the production-ready version of this project at ClimbsRocks/auto_ml

Compilation of R and Python programming codes on the Data Professor YouTube channel.

HungaBunga: Brute-Force all sklearn models with all parameters using .fit .predict!

Titanic assignment on Kaggle competition

Machine Learning inference engine for Microcontrollers and Embedded devices

Python for chemoinformatics

Collection of Kaggle Datasets ready to use for Everyone (Looking for contributors)

Predicting the winner of 2019 cricket world cup using random forest algorithm

Embed visualizations and code from Observable notebooks in Jupyter

A python package to assess cluster tendency

Swift kernel for Google Colaboratory

A comprehensive dimensional reduction framework to recover the latent topology from high-dimensional data.

Spawn JupyterHub single-user notebook servers with systemd

Jupyter Notebooks and miscellaneous

Using machine learning libraries to analyze NBA data

Notes and tutorials on how to use python, pandas, seaborn, numpy, matplotlib, scipy for data science.

Machine Learning in .NET Core.

Quora Kaggle Competition : Natural Language Processing using word2vec embeddings, scikit-learn and xgboost for training

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machine_learning_examples

Librería para la evaluación de calidad de datos, e interacción con el portal de datos.gov.co

Dockerize and deploy machine learning model as REST API using Flask

datascienv 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

JupyterLab desktop application, based on Electron.

Implementations of machine learning algorithm by Python 3