Oladele01's Stars
ligerfotis/CSE6363_Machine_Learning
Machine Learning algorithms from-scratch implementation. It covers most Supervised and Unsupervised algorithms. Homework assignments and Projects for graduate level Machine Learning Course taught by Dr Manfred Huber at UTA during Spring 21
rockthejvm/scala-at-light-speed
The repository for the free Scala at Light Speed mini-course
DataScienceNigeria/DSN-AI-Bootcamp-2023-Qualification-Project-Participation-and-Hackathon
sheriffff/teaching_ibm_skillup_data_analytics2023
SPLWare/esProc
esProc SPL is a scripting language for data processing, with well-designed rich library functions and powerful syntax, which can be executed in a Java program through JDBC interface and computing independently.
DataTalksClub/data-engineering-zoomcamp
Free Data Engineering course!
solita/dev-academy-2023-exercise
An exercise for Solita Dev Academy 2023
pddasig/Machine-Learning-Competition-2020
SPWLA PDDA’s 1st Petrophysical Data-Driven Analytics Contest -- Sonic Log Synthesis
Oladele01/2016-ml-contest
Machine learning contest - October 2016 TLE
KolatimiDave/Expresso-Customer-Churn-Prediction
This repository explains how to predict customer churn. An Hackathon Organized by Data Science Nigeria(DSN-AI) to help Expresso predict customer Churn. My 2nd place solution, log_loss of 0.246675. I've also added a section in the notebook to get a score of 0.246643, which could be the unofficial 1st place solution.
marxprop/Winning-Solution-Expresso-Churn-Prediction-Challenge-by-DSN
Hackathon Solution for the Expresso Churn Prediction Challenge by Data Science Nigeria
vecxoz/vecstack
Python package for stacking (machine learning technique)
kinverarity1/lasio-notebooks
IPython notebooks for learning how to use lasio
agilescientific/welly
Welly helps with well loading, wireline logs, log quality, data science
softwareunderground/52things
52 Things You Should Know About Geocomputing
geopandas/geopandas
Python tools for geographic data
donnemartin/data-science-ipython-notebooks
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.
GokuMohandas/Made-With-ML
Learn how to design, develop, deploy and iterate on production-grade ML applications.
floodsung/Deep-Learning-Papers-Reading-Roadmap
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
pytorch/pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
opencv/opencv
Open Source Computer Vision Library
keras-team/keras
Deep Learning for humans
tensorflow/tensorflow
An Open Source Machine Learning Framework for Everyone
TarrySingh/Artificial-Intelligence-Deep-Learning-Machine-Learning-Tutorials
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.
justmarkham/scikit-learn-videos
Jupyter notebooks from the scikit-learn video series
PipelineAI/pipeline
PipelineAI
automl/auto-sklearn
Automated Machine Learning with scikit-learn
Yorko/mlcourse.ai
Open Machine Learning Course
dive-into-machine-learning/dive-into-machine-learning
Free ways to dive into machine learning with Python and Jupyter Notebook. Notebooks, courses, and other links. (First posted in 2016.)
ageron/handson-ml
⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 instead.