KaplanEmrah's Stars
EpistasisLab/tpot
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
bayesian-optimization/BayesianOptimization
A Python implementation of global optimization with gaussian processes.
leriomaggio/deep-learning-keras-tensorflow
Introduction to Deep Neural Networks with Keras and Tensorflow
rasbt/deep-learning-book
Repository for "Introduction to Artificial Neural Networks and Deep Learning: A Practical Guide with Applications in Python"
dipanjanS/practical-machine-learning-with-python
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.
LiYangHart/Hyperparameter-Optimization-of-Machine-Learning-Algorithms
Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models (easy&clear)
ScottfreeLLC/AlphaPy
Python AutoML for Trading Systems and Sports Betting
joeddav/devol
Genetic neural architecture search with Keras
giswqs/qgis-earthengine-examples
A collection of 300+ Python examples for using Google Earth Engine in QGIS
sudharsan13296/Hands-On-Reinforcement-Learning-With-Python
Master Reinforcement and Deep Reinforcement Learning using OpenAI Gym and TensorFlow
dipanjanS/hands-on-transfer-learning-with-python
Deep learning simplified by transferring prior learning using the Python deep learning ecosystem
stratospark/food-101-keras
Food Classification with Deep Learning in Keras / Tensorflow
shamangary/SSR-Net
[IJCAI18] SSR-Net: A Compact Soft Stagewise Regression Network for Age Estimation
gee-community/qgis-earthengine-plugin
Integrates Google Earth Engine and QGIS using Python API
anitagraser/QGIS-resources
Collection of QGIS resources featured on my blog
cavalab/srbench
A living benchmark framework for symbolic regression
chendaniely/scipy-2019-pandas
Pandas tutorial for SciPy 2019
wojdyr/xylib
library for reading files with x-y data from powder diffraction, spectroscopy, or other experimental methods
OValery16/gender-age-classification
gender/age classification
sybila/presentation-template
Simple presentation template.
yezhilengyue/Python_ML_Practice
Following the instruction of "Machine Learning Mastery With Python"
randlab/geone
DeeSse interface, utilities and examples
mjain72/Hyperparameter-tuning-in-XGBoost-using-genetic-algorithm
MichaelCHarrison/XGBoost-with-Python-Notes
Notes on XGBoost
ColeSlawBecky/Kriging-in-python
Additions to the pykrige.py already available here: https://github.com/bsmurphy/PyKrige
shahriya1995/HousePricePrediction
House Prediction using Both Images and Textual Information - Keras Functional API, Neural Networks, CNN
guilhermevescovi/House-Prices-Advanced-Regression-Techniques
A machine learning project related to house prices predictions. The main techniques of this project are Feature engineering, Random Forest, Gradient Boosting, Keras, TensorFlow and advanced regression techniques.
sean578/hands_on_machine_learning
Code while working through 'Hands on machine learning with Scikit-Learn, Keras and TensorFlow' book.
techedgaurav/House-Price-prediction-using-Keras
Ask a home buyer to describe their dream house, and they probably won't begin with the height of the basement ceiling or the proximity to an east-west railroad. But this playground competition's dataset proves that much more influences price negotiations than the number of bedrooms or a white-picket fence. With 79 explanatory variables describing (almost) every aspect of residential homes in Ames, Iowa, this competition challenges you to predict the final price of each home.
analyticsvidhya/Complete-Guide-to-Parameter-Tuning-in-XGBoost-with-codes-in-Python