bchalamayya

bchalamayya's Stars

• bchalamayya/generative-ai-for-beginners

  12 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/

  1

• bchalamayya/Womanium-Quantum-Hackathon-2022

  1

• SkalskiP/courses

  This repository is a curated collection of links to various courses and resources about Artificial Intelligence (AI)

  Language:Python5.3k476

• SkalskiP/SkalskiP

  3012

• THU-BPM/chatgpt-sql

  The prediction results of ChatGPT on various datasets of Text-to-SQL.

  Language:Python988

• eosphoros-ai/DB-GPT

  AI Native Data App Development framework with AWEL(Agentic Workflow Expression Language) and Agents

  Language:Python13.3k1.8k

• bchalamayya/notebooks

  Examples and tutorials on using SOTA computer vision models and techniques. Learn everything from old-school ResNet, through YOLO and object-detection transformers like DETR, to the latest models like Grounding DINO and SAM.

  1

• chenfei-wu/TaskMatrix

  Language:Python34.5k3.3k

• faridrashidi/kaggle-solutions

  🏅 Collection of Kaggle Solutions and Ideas 🏅

  Language:HTML4k1.5k

• GokuMohandas/Made-With-ML

  Learn how to design, develop, deploy and iterate on production-grade ML applications.

  Language:Jupyter Notebook37.1k5.9k

• microsoft/nlp-recipes

  Natural Language Processing Best Practices & Examples

  Language:Python6.4k916

• aws-solutions-library-samples/guidance-for-training-an-aws-deepracer-model-using-amazon-sagemaker

  DeepRacer workshop content. This Guidance demonstrates how software developers can use an Amazon SageMaker Notebook instance to directly train and evaluate AWS DeepRacer models with full control

  Language:Jupyter Notebook1.2k714

• bchalamayya/Learn_Machine_Learning_in_3_Months

  This is the code for "Learn Machine Learning in 3 Months" by Siraj Raval on Youtube

  1

• bchalamayya/Data-Science--Cheat-Sheet

  Cheat Sheets

  1

• bansalkanav/python_notes

  Language:Jupyter Notebook164129

• RubensZimbres/Repo-2016

  R, Python and Mathematica Codes in Machine Learning, Deep Learning, Artificial Intelligence, NLP and Geolocation

  Language:Python106113

• s-heisler/pycon2017-optimizing-pandas

  Materials for PyCon 2017 presentation on optimizing Pandas code

  Language:Jupyter Notebook215145

• antonmks/nvParse

  Fast, gpu-based CSV parser

  Language:Cuda55826

• BurntSushi/xsv

  A fast CSV command line toolkit written in Rust.

  Language:Rust10.3k318

• dmlc/xgboost

  Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow

  Language:C++26.1k8.7k

• bchalamayya/fairseq

  Facebook AI Research Sequence-to-Sequence Toolkit

  Language:Lua1

• electroly/sqlnotebook

  Casual data exploration in SQL

  Language:C#59035

• facebookresearch/fairseq-lua

  Facebook AI Research Sequence-to-Sequence Toolkit

  Language:Lua3.7k615

• lucidworks/banana

  Banana for Solr - A Port of Kibana

  Language:JavaScript669235

• bchalamayya/aws-cli

  Universal Command Line Interface for Amazon Web Services

  Language:Python1

• sih4sing5hong5/google-sites-liberation

  Fork Version: This is an import/export tool for Google Sites.

  Language:Java13232

• Far0n/kaggletils

  Language:Python381154

• zhiwehu/Python-programming-exercises

  100+ Python challenging programming exercises

  26.6k6.8k

• fnielsen/afinn

  AFINN sentiment analysis in Python

  Language:Jupyter Notebook446223

• fivethirtyeight/data

  Data and code behind the articles and graphics at FiveThirtyEight

  Language:Jupyter Notebook16.8k10.9k