Jyosna's repositories
Applied-Data-Science-Capstone
IBM Data Science Professional Certificate
ChainLadder
:exclamation: This is a read-only mirror of the CRAN R package repository. ChainLadder — Statistical Methods and Models for Claims Reserving in General Insurance. Homepage: https://github.com/mages/ChainLadder#chainladder Report bugs for this package: https://github.com/mages/ChainLadder/issues
ChainLadder-1
Claims reserving models in R
chainladder-python
Actuarial reserving in Python
cool_python_apps
Small and cool python apps including bitcoin mining, language translator etc.
Data-Science--Cheat-Sheet
Cheat Sheets
data-structures-algorithms-python
This tutorial playlist covers data structures and algorithms in python. Every tutorial has theory behind data structure or an algorithm, BIG O Complexity analysis and exercises that you can practice on.
DataAnalysisProjects
This contains data analysis projects
deep-learning-keras-tf-tutorial
Learn deep learning with tensorflow2.0, keras and python through this comprehensive deep learning tutorial series. Learn deep learning from scratch. Deep learning series for beginners. Tensorflow tutorials, tensorflow 2.0 tutorial. deep learning tutorial python.
hungry
Hungry code for git and github demonstration
intro-html
A robot powered training repository :robot:
math-for-machine-learning
Statistics and math for machine learning and data science
potato-disease-classification
Potato Disease Classification - Training, Rest APIs, and Frontend to test.
PPL_Python_Training
Repository to host code for princeton public library python training
practical-statistics-for-data-scientists
Code repository for O'Reilly book
py
Repository to store sample python programs for python learning
python-simple-ocr-project
A simple OCR Project using python with frontend in VueJS
python_projects
Repository for python projects
Seaborn-Series
This is the code for the Seaborn Series on the Skillbasics YouTube channel
simfin-tutorials
Tutorials for SimFin - Simple financial data for Python
ThinkStats2
Text and supporting code for Think Stats, 2nd Edition