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  • šŸ‘‹ Hi, Iā€™m @ravindrareddytamma
  • šŸ‘€ Iā€™m interested in machine learning, data sciences and latest technologies
  • šŸŒ± Iā€™m currently learning deep learning
  • šŸ’žļø Iā€™m looking to collaborate on anything that makes this world a better place to live.
  • šŸ“« How to reach me mail:[email protected]

TAMMA RAVINDRA REDDY's Projects

amazon-sagemaker-examples icon amazon-sagemaker-examples

Example notebooks that show how to apply machine learning, deep learning and reinforcement learning in Amazon SageMaker

d3 icon d3

Bring data to life with SVG, Canvas and HTML. :bar_chart::chart_with_upwards_trend::tada:

dataframesummary icon dataframesummary

A R Package that can be readily installed to get Numerical and Factor Summary of Columns in a DataFrame

datasets icon datasets

Datasets that I generally use for trainings, workshops

decipheringcryptocurrency icon decipheringcryptocurrency

The case is financial time-series prediction with cryptocurrencies and it integrates knowledge from various sources - Crypto Currencies, Quantitative Finance, and Machine learning. The data consists of time-series of various cryptocurrencies with open, high, low, close prices and volumes from different crypto exchanges. The goal is to build a successful investing/trading model on the cryptocurrency markets.

hive icon hive

Practiced Hive Queries along with Databases

llm_notes icon llm_notes

Quick References and Detailed Notes on LLM's

modelmetrics icon modelmetrics

Contains all the required metrics for a classification model

pandas icon pandas

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

python-assignment icon python-assignment

Basics of Python Subsetting and Filtering as well as little bit DV with Python

shap icon shap

A game theoretic approach to explain the output of any machine learning model.

stats-using-r icon stats-using-r

A complete repository that can be used as reference for implementing statistics using R

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