Alexander Grablevski (alexander-gr)

alexander-gr

Geek Repo

Company:@santiment

Location:Planet Earth

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Alexander Grablevski's starred repositories

brownie

A Python-based development and testing framework for smart contracts targeting the Ethereum Virtual Machine.

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croniter-fork

croniter is a python module to provide iteration for datetime object.

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neural_prophet

NeuralProphet: A simple forecasting package

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node2vec

Implementation of the node2vec algorithm.

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shap

A game theoretic approach to explain the output of any machine learning model.

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transformers

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

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mlfinlab

MlFinLab helps portfolio managers and traders who want to leverage the power of machine learning by providing reproducible, interpretable, and easy to use tools.

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chow_test

Python module to calculate time series Chow break statistics.

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obm

Async blockchain nodes interacting tool with ORM-like API.

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hacker-laws

💻📖 Законы, теории, принципы и модели, которые полезно знать разработчику.

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awesome-public-datasets

A topic-centric list of HQ open datasets.

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sanpy

Santiment API Python Client

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ethereum-streaming-analytics-demo

Process Ethereum data with Pubsub and Dataflow

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zipline

Zipline, a Pythonic Algorithmic Trading Library

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dash_sample_dashboard

Build a Complex Reporting Dashboard using Dash and Plotly

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pycon-pandas-tutorial

PyCon 2015 Pandas tutorial materials

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SNAT

Social Network AntiTroll

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troll2vec

Convolutional neural network for toxicity classification. Works with russian language

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catboost

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

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pandas

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

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DataScience

Blockchain researches on demand

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facenet

Face recognition using Tensorflow

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