Pinned Repositories
10-steps-to-become-a-data-scientist
📢 Ready to learn! you will learn 10 skills as data scientist:📚 Machine Learning, Deep Learning, Data Cleaning, EDA, Learn Python, Learn python packages such as Numpy, Pandas, Seaborn, Matplotlib, Plotly, Tensorfolw, Theano...., Linear Algebra, Big Data, Analysis Tools and solve some real problems such as predict house prices.
article-downloader
Uses publisher APIs to programmatically retrieve scientific journal articles for text mining.
awesome-deep-learning-papers
The most cited deep learning papers
awesome-twitter-data
A list of Twitter datasets and related resources.
baselines
OpenAI Baselines: high-quality implementations of reinforcement learning algorithms
bc18-scaffold
bdr-tweet
Mining Twitter for Disaster Response
numpy_ringbuffer
Ring-buffer implementation that thinly wraps a numpy array
ringbuffer
Ring buffer that allows for high-throughput data transfer between multiproccessing Python processes.
TensorExpand
集成包
illiaKavalevich's Repositories
illiaKavalevich/numpy_ringbuffer
Ring-buffer implementation that thinly wraps a numpy array
illiaKavalevich/ringbuffer
Ring buffer that allows for high-throughput data transfer between multiproccessing Python processes.
illiaKavalevich/TensorExpand
集成包
illiaKavalevich/10-steps-to-become-a-data-scientist
📢 Ready to learn! you will learn 10 skills as data scientist:📚 Machine Learning, Deep Learning, Data Cleaning, EDA, Learn Python, Learn python packages such as Numpy, Pandas, Seaborn, Matplotlib, Plotly, Tensorfolw, Theano...., Linear Algebra, Big Data, Analysis Tools and solve some real problems such as predict house prices.
illiaKavalevich/article-downloader
Uses publisher APIs to programmatically retrieve scientific journal articles for text mining.
illiaKavalevich/awesome-deep-learning-papers
The most cited deep learning papers
illiaKavalevich/awesome-twitter-data
A list of Twitter datasets and related resources.
illiaKavalevich/baselines
OpenAI Baselines: high-quality implementations of reinforcement learning algorithms
illiaKavalevich/bc18-scaffold
illiaKavalevich/bert
TensorFlow code and pre-trained models for BERT
illiaKavalevich/coursera_SDA_yandex
A repository with my solutions of Coursera course "Introduction to Machine Learning" by School of Data Analysis of Yandex
illiaKavalevich/deep-learning-with-python-notebooks
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
illiaKavalevich/gensim
Topic Modelling for Humans
illiaKavalevich/Hands-On-Deep-Learning-Algorithms-with-Python
Hands-On Deep Learning Algorithms with Python, By Packt
illiaKavalevich/homemade-machine-learning
🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained
illiaKavalevich/ml-course-hse
Машинное обучение на ФКН ВШЭ
illiaKavalevich/ml-course-msu
Lecture notes and code for Machine Learning practical course on CMC MSU
illiaKavalevich/nbdev
Create delightful python projects using Jupyter Notebooks
illiaKavalevich/nlp-datasets
Alphabetical list of free/public domain datasets with text data for use in Natural Language Processing (NLP)
illiaKavalevich/nlp-in-practice
NLP, Text Mining and Machine Learning starter code to solve real world text data problems. Includes: Gensim Word2Vec, phrase embeddings, keyword extraction with TFIDF, Text Classification with Logistic Regression, word count with pyspark, simple text preprocessing, pre-trained embeddings and more.
illiaKavalevich/predictive-maintenance
Demonstration of MapR for Industrial IoT
illiaKavalevich/proj_news_viz
illiaKavalevich/reinforcement-learning
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
illiaKavalevich/s2
Python wrapper for the Semantic Scholar API
illiaKavalevich/semantic-scholar-scrapper
A Scrapper for Semantic Scholar.
illiaKavalevich/SPADE
Semantic Image Synthesis with SPADE
illiaKavalevich/The-Elements-of-Statistical-Learning-Python-Notebooks
A series of Python Jupyter notebooks that help you better understand "The Elements of Statistical Learning" book
illiaKavalevich/theMLbook
The Python code to reproduce the illustrations from The Hundred-Page Machine Learning Book.
illiaKavalevich/whisker_model
Codes for reproducing results in paper: https://arxiv.org/abs/1706.07555
illiaKavalevich/xlinkBook
a web base research management tool that deal with big data for everyone