arif-eker's Stars
Avik-Jain/100-Days-Of-ML-Code
100 Days of ML Coding
GokuMohandas/Made-With-ML
Learn how to design, develop, deploy and iterate on production-grade ML applications.
AMAI-GmbH/AI-Expert-Roadmap
Roadmap to becoming an Artificial Intelligence Expert in 2022
ageron/handson-ml2
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
afshinea/stanford-cs-229-machine-learning
VIP cheatsheets for Stanford's CS 229 Machine Learning
dair-ai/ML-YouTube-Courses
📺 Discover the latest machine learning / AI courses on YouTube.
mml-book/mml-book.github.io
Companion webpage to the book "Mathematics For Machine Learning"
Atcold/NYU-DLSP20
NYU Deep Learning Spring 2020
afshinea/stanford-cs-230-deep-learning
VIP cheatsheets for Stanford's CS 230 Deep Learning
adamerose/PandasGUI
A GUI for Pandas DataFrames
nerdyrodent/VQGAN-CLIP
Just playing with getting VQGAN+CLIP running locally, rather than having to use colab.
afshinea/stanford-cs-221-artificial-intelligence
VIP cheatsheets for Stanford's CS 221 Artificial Intelligence
krzjoa/awesome-python-data-science
Probably the best curated list of data science software in Python.
google-research-datasets/Objectron
Objectron is a dataset of short, object-centric video clips. In addition, the videos also contain AR session metadata including camera poses, sparse point-clouds and planes. In each video, the camera moves around and above the object and captures it from different views. Each object is annotated with a 3D bounding box. The 3D bounding box describes the object’s position, orientation, and dimensions. The dataset contains about 15K annotated video clips and 4M annotated images in the following categories: bikes, books, bottles, cameras, cereal boxes, chairs, cups, laptops, and shoes
CamDavidsonPilon/lifetimes
Lifetime value in Python
WillKoehrsen/wikipedia-data-science
Working with and analyzing Wikipedia Data
yazbel/python-istihza
İstihza Python Belgeleri, en kapsamlı Türkçe Python belgelendirmesi
sibirbil/IMO2020
İstanbul'da Makine Öğrenmesi (27 Ocak- 2 Şubat, 2020) - Ders malzemeleri
cobanov/paul-graham-turkce
Bu repo paulgraham.com adresindeki denemelerin Turkceye cevrilmis hallerinin yayinladigi gonulluluk ile buyuyen bir kaynaktir.
ayyucekizrak/turkce-derin-ogrenme-kaynaklari
Türkiye'de yapılan derin öğrenme (deep learning) ve makine öğrenmesi (machine learning) çalışmalarının derlendiği sayfa.
msahamed/handle_imabalnce_class
Address imbalance classes in machine learning projects.
tevfikaytekin/data_science
waylow/boneWidget
Blender add-on for making bone shape
AhmetFurkanDEMIR/DEncrypt-21
Image encryption and embedding encrypted text in the image.
principai/NLP_PAI
PAI code repo for NLP researchers
ayyucekizrak/yapay-ogrenme-sozlugu
Yapay Öğrenme Terimlerini Türkçe ve İngilizce olarak arama yapabileceğiniz çevrimiçi sözlük
ayyucekizrak/turkce-yapay-zeka-terimleri
Çalışmalarınızda kullanabileceğiniz Türkçe Yapay Zeka Terimleri.
batux/AI_ML_DeepLearning
AI ML DeepLearning Sunum
cosgunhalil/arkanoid-clone
frknklcsln/Breast-Cancer-Prediction
Breast cancer is one of the most common cancers with a high mortality rate among women. Therefore, an accurate and reliable system is necessary for the early diagnosis of this cancer. This repository presents a comparison of four machine learning (ML) algorithms:Logistic Regression (LR), Nearest Neighbor Classifier (k-NN), Random Forest Classifier (RFC), Naïve Bayes (NB) on the Wisconsin Diagnostic Breast Cancer (WDBC) dataset by measuring their classification test and cross-validation accuracy.