6120 Open source projects that are alternatives of or similar to Compling_nlp_hse_course

⚛ 10 week Practical Course on Quantum Information Science and Quantum Computing - with Qiskit and IBMQX

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General Assembly's 2015 Data Science course in Washington, DC

USC urban data science course series with Python and Jupyter

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Notes for getting to know the Julia programming language in one day.

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This repo contains my coursework, assignments, and Slides for Natural Language Processing Specialization by deeplearning.ai on Coursera

Curso Maestro Python 3 en Udemy (20 horas)

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适合初级到中级晋升者，有了体系之后就看熟练度了。

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statistics and classes for exploratory spatial data analysis

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A short tutorial for Torchtext, the NLP-specific add-on for Pytorch.

My repository for the Carvana Image Masking Challenge

COVID-19 workflows and datasets.

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Machine learning projects, often on audio datasets

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This is the code for "Simple Blockchain in 5 Minutes" By Siraj Raval on Youtube

Inference case studies in jupyter

Computer Science SCHOOL resources

GANs in slanted land

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CAUTION: This is not maintained anymore. Visit https://github.com/chainer-community/chainer-colab-notebook/

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Kaggle Quora Questions Pairs Competition

Project to train/test convolutional neural networks to extract buildings from SpaceNet satellite imageries.

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The art of using t-SNE for single-cell transcriptomics

Bert-base NLP pipeline for Turkish, Ner, Sentiment Analysis, Question Answering etc.

Tianchi medical AI competition [Season 1]: Lung nodules image segmentation of U-Net. U-Net训练基于卷积神经网络的肺结节分割器

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ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

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