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Name: Satish Rohit Singh

Type: User

Company: IgniteCPP

Bio: 🇦🇪 based Lead Data Scientist and AI Engineer. Bridging the gap between Machines🤖 and Humans🧠, one model and one prompt at a time.

Location: Dubai, United Arab Emirates

Blog: https://linkedin.com/in/satish-r-singh/

I am currently working as a Lead Data Scientst at Ignite. I come with an extensive experience of working with different technologies including Data Science, Machine Learning and Deep Learning, NLP, Data Engineering.

Things I'm good at 🔥

Domain: Deep Learning, Natural Language Processing, Image Processing, Machine Learning, Data Science, Data Wrangling, Data Visualization, Data Engineering and Data Warehousing.

Languages: Python, SQL, Scala, Sqoop, Flume, Pig.

Libraries & Tools: Pandas, Scikit-Learn, SciPy, Matplotlib, NumPy, PyTorch, Keras, TensorFlow, NLTK.

Data Analysis: Exploratory Data Analysis, Ensemble Methods, Strong Statistical Foundation, Model Development & Evaluation Metrics, Quantitative Methods.

Cloud: AWS, Azure.

"Nothing of significance was ever achieved by an individual acting alone."

John C. Maxwell

Without the 1000s of years of collaboration between like minded humans, we as a civilization wouldn't be too far from the apes we have evolved from. If you think WE can together make a difference for good, reach out to me now.

Find my peronal Data Science projects here Data Science Playground.

Find me on

Satish Rohit Singh's Projects

amazon-fraud-detector-end-to-end

Sample datasets and code for operationalizing Amazon Fraud Detector using SageMaker DataWrangler, Feature Store, and Pipelines.

amazon-sagemaker-built-in-algorithms-mlops-pipeline-using-aws-cdk

MLOps Pipeline Using SageMaker & CDK, where models are from SageMaker built-in algorithms.

amazon-sagemaker-deepar-mlops-pipeline-cdk

This CDK implementation demonstrates how MLOps workflow for Time Series Forecasting with SageMaker Built-in DeepAR can be automated with AWS Serverless Services.

amazon-sagemaker-forecasting-air-pollution-with-deepar

amazon-sagemaker-mlops-with-featurestore-and-datawrangler

awesome-mlops

A curated list of references for MLOps

awesome-mlops-1

:sunglasses: A curated list of awesome MLOps tools

awesome-public-datasets

A topic-centric list of HQ open datasets.

aws-sagemaker

az-900

Quick reference for AZ900 certification

bodyshaming_classification

bostonhousepricing

Boston House Pricing

cheat-sheets

Various cheat sheets I have found on internet for easy reference

clean-code-ml

:bathtub: Clean Code concepts adapted for machine learning and data science. Now a free video series 😎 https://bit.ly/2yGDyqT

confludent-tutorial

data-science-for-beginners

10 Weeks, 20 Lessons, Data Science for All!

data-science-playground

A brief showcase of all the Data Science Projects done by me for various reasons.

deep-learning-drizzle

Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

google-images-download

Python Script to download hundreds of images from 'Google Images'. It is a ready-to-run code!

gpt4-pdf-chatbot-langchain

GPT4 & LangChain Chatbot for large PDF docs

helpful

Config files for my GitHub profile.

incidentsdataset

Code and data (Incidents Dataset) for ECCV 2020 Paper "Detecting natural disasters, damage, and incidents in the wild".

ipynbrenderer

ml-for-beginners

12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

mr.-ranedeer-ai-tutor

A GPT-4 AI Tutor Prompt for customizable personalized learning experiences.

online-repo

demo repo for git training

openai-quickstart-python

pythondatasciencehandbook

Python Data Science Handbook: full text in Jupyter Notebooks

readme-typing-svg

⚡ Dynamically generated, customizable SVG that gives the appearance of typing and deleting text. Typing SVGs can be used as a bio on your Github profile readme or repository.

sagemaker-end-to-end-workshop

Hands-on end-to-end workshop to explore Amazon SageMaker.

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