🔭 Techie since 2006!
📫 How to reach me: Connect with me on LinkedIn.
😄 Pronouns: He/Him
cmaz83 Goto Github PK
Name: Chiranjib Mazumdar
Type: User
Chiranjib Mazumdar's Projects
ai-102-aiengineer
Lab files for AI-102 - AI Engineer
ai102files
aiengineer_coursera
azure-mobile-apps-quickstarts
Client and server templates for Azure Mobile Apps
azure-openai-sql
botbuilder-samples
Welcome to the Bot Framework samples repository. Here you will find task-focused samples in C#, JavaScript and TypeScript to help you get started with the Bot Framework SDK!
botframework-composer
Dialog creation and management for Microsoft Bot Framework Applications
calculator
A node.js demo application
cmaz83
cmaz83.github.io
cmmi-document-template
📖 Document Template for capability maturity model integration
cognitive-services-python-sdk-samples
Learn how to use the Cognitive Services Python SDK with these samples
cognitive-services-quickstart-code
Code Examples used by the Quickstarts in the Cognitive Services Documentation
courses
Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1
data-analyst-skill-with-videos-in-2021
data-science-best-practices
The goal of this repository is to enable data scientists and ML engineers to develop data science use cases and making it ready for production use. This means focusing on the versioning, scalability, monitoring and engineering of the solution.
data-science-for-beginners
10 Weeks, 20 Lessons, Data Science for All!
datacamp-baseball-analysis
datacamp-nobel-analysis
datascience
datasciencecoursera
This repository was created as part of a project for a related Coursera course.
datasharing
The Leek group guide to data sharing
fabricpractice
first_streamlit_app
freecodecamp-intro-to-pandas
generative-ai-for-developers
Creating Apps with the ChatGPT API
gfpgan
GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.
kcna
ml-for-beginners
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
ml-foundations
Machine Learning Foundations: Linear Algebra, Calculus, Statistics & Computer Science
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