Alink is the Machine Learning algorithm platform based on Flink, developed by the PAI team of Alibaba computing platform.
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Updated
May 23, 2024 - Java
Alink is the Machine Learning algorithm platform based on Flink, developed by the PAI team of Alibaba computing platform.
大规模中文自然语言处理语料 Large Scale Chinese Corpus for NLP
This project aims to simplify and summarize scientific data , convert it to a audio format as a podcast , and create a power point presentation from the paper. This helps researchers, academics and students altogether.
A binary analysis tool for identifying unknown function names, using a word-2-vec model
Explore NLP model evaluation on answer scores and tweet sentiment. Features preprocessing, BoW, TF-IDF, Word2Vec, and models like Linear Regression, Decision Tree, SVM, Logistic Regression, and Random Forest.
Web-ify your word2vec: framework to serve distributional semantic models online
Topic Modelling for Humans
A basic word-embedding model to find best matching students or professors, and recommend the top n results to a specific student
Toolkit to obtain and preprocess German text corpora, train models and evaluate them with generated testsets. Built with Gensim and Tensorflow.
NLP use cases using popular solutions: Frequency Embeddings, Word embedding (word2vec, doc2vec, Glove), RNN,LSTM, Transformers-BERT, Sentence_Transformers etc. PyTorch
Jupyter notebooks for the Deep Learning course that is held at FEI, VSB-TU Ostrava
Implemented projects from noncontextual word embeddings like Word2Vec to contextual word embeddings like ELMO, GPT, BERT to solving NLP tasks Sentence Level Classification (sentimental analysis & Toxic comment classification), Token Level Classification (POS Tagging, NER Tagging), Machine Translation (MT)
This Repository contains the Data Science things I have done in recent times along with visualization , cleaning , models, statistics, Courses, Datasets. :=)
Quranic Lexical/Semantic Search
Unigram Part-of-Speech Tagging using Support Vector Machines and Word Embedding Features
Keras, PyTorch, and NumPy Implementations of Deep Learning Architectures for NLP
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