Heorhii's repositories
awesome-readme
A guide to writing an Awesome README. Read the full article in Towards Data Science.
cookiecutter-data-science
Cookiecutter for the Team Data Science Process (TDSP).
courses
Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1
deep-nlp
Natural Language Processing with Deep Learning
Deep-Tutorials-for-PyTorch
In-depth tutorials for implementing deep learning models on your own with PyTorch.
deep_learning_2018-19
Официальный репозиторий курса Deep Learning (2018-2019) от Deep Learning School при ФПМИ МФТИ
deeplearning-models
A collection of various deep learning architectures, models, and tips
dls_school2
Homework and projects
ds-fundamentals
Coding materials for DS Fundamentals Course
education
Materials for my lectures and for self-study in machine learning
examples-counterexamples
Machine learning examples and counterexamples
Global-Wheat-Detection
Showcases the use of deep learning to detect wheat heads from crops. The project is based on: https://www.kaggle.com/c/global-wheat-detection.
invst_mgmt_w_py
Investment mangement with python coursera from coursera
LeetCodeProblems
LeetCode Problems
ml_uwr
Materials for my Machine Learning course at University of Wroclaw
MLAlgorithms
Minimal and clean examples of machine learning algorithms implementations
pdf_downloader
Download pdfs from a website with Python
Practical_ML_WS19
Lecture materials and notebooks for the Pattern Analysis and Machine Intelligence machine learning praktikum in the winter semester 2019/2020 at Goethe University
pytorch-seq2seq
Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.
recmetrics
A library of metrics for evaluating recommender systems
stockpredictionai
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
StudyBook
Study E-Book(ComputerVision DeepLearning MachineLearning Math NLP Python ReinforcementLearning)
TestCase
sql test scripts