Mahesh Jadhav's repositories
Text-Analysis
Basic text analysis, Topic mining, wordcloud and Cog creation,webscraping
26-Weeks-Of-Data-Science
Email Newsletter
Automatic-Question-Answer-Generation
A rule based system system for automatically generating Factoid question Answers based on "A rule based question generation framework to deal with simple and complex sentences" by Das et.al
BERTopic
Leveraging BERT and c-TF-IDF to create easily interpretable topics.
MLOps
It contains tutorial of various MLOps algorithm. Will update it as soon as I learn something new. Happy Learning.
speech-to-text
Speech to Text with Hugging Face and Wav2vec 2.0
Text-Analytics
NLP Classification of Tweets (Twitter Data)
transformers
🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.
Bart_T5-summarization
Summarization Task using Bart and T5 models.
BERT-SQuAD
SQuAD Question Answering Using BERT, PyTorch
BERT_generate_grammar_MCQ_from_news_article
Use pretrained BERT model to automatically generate grammar multiple choice questions (MCQ) from any news article or story.
BERTSimilarity
Sentential Semantic Similarity measurement library using BERT Embeddings for spatial distance evaluation.
CarND-Vehicle-Detection
Vehicle Detection Project
ClusterTransformer
Topic clustering library built on Transformer embeddings and cosine similarity metrics.Compatible with all BERT base transformers from huggingface.
Content-Based-Recommendation---Good-Reads-data
Content Based Recommendation using Good read data
Data-Mining--Unsupervised-Learning
Data Mining- Unsupervised Learning -Clustering
Data-Mining-Unsupervised-learning
Data Mining- Unsupervised Learning -Association Rules-market basket analysis
deep_autoviml
Build tensorflow keras model pipelines in a single line of code. Created by Ram Seshadri. Collaborators welcome. Permission granted upon request.
deploy_dl_models_to_production_on_AWS
Tutorial to deploy Deep Learning Model to Production on AWS with Docker and Elastic Beanstalk
End-to-end-Youtube-audio-translation-aws-serverless
All the serverless code necessary to convert the audio of a Youtube video in one language to a different language using AWS
generate_boolean_questions_using_T5_transformer
Generating boolean (yes/no) questions from any content using T5 text-to-text transformer model and BoolQ dataset
Generate_MCQ_BERT_Wordnet_Conceptnet
Generate Multiple choice Questions from any content or news article using BERT Extractive Summarization, Wordnet and Conceptnet
Generate_True_or_False_OpenAI_GPT2_Sentence_BERT
Generate True or False questions from any content with OpenAI GPT2 text generation, Sentence-BERT semantic search and Berkley constituency parser.
Getting-Started-with-Google-BERT
Build and train state-of-the-art natural language processing models using BERT
MiniAttention
Hierarchical Attention Layer for Keras for document classification.
Questgen.ai
Question generation using state-of-the-art Natural Language Processing algorithms
speech-recognition-neural-network
This is the end-to-end Speech Recognition neural network, deployed in Keras. This was my final project for Artificial Intelligence Nanodegree @Udacity.