dmkarthiksrini's Stars
bitnami/containers
Bitnami container images
boisalai/de-zoomcamp-2023
github/gitignore
A collection of useful .gitignore templates
aaryahjolia/dsa_competitive-coding
A repository to learn deep competitive coding algorithms along with DSA.
tirthajyoti/Data-science-best-resources
Carefully curated resource links for data science in one place
andrey-pohilko/registry-cli
Scripts for easy manipulation of docker-registry from command line (and from scripts)
dmkarthiksrini/dmkarthiksrini.github.io
Asabeneh/30-Days-Of-Python
30 days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than100 days, follow your own pace. These videos may help too: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw
awesomedata/awesome-public-datasets
A topic-centric list of HQ open datasets.
xephonhq/awesome-time-series-database
:clock7: A curated list of awesome time series databases, benchmarks and papers
dmkarthiksrini/DS-Learning
Learning Notes for Data structures
dmkarthiksrini/data-engineering-zoomcamp
Free Data Engineering course!
dmkarthiksrini/data-science-ipython-notebooks
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
dmkarthiksrini/cheatsheets
RStudio Cheat Sheets
dmkarthiksrini/MachineLearning-Projects
dmkarthiksrini/Critical_Data_Ananlysis_dummy
This is a model of housing prices based using multiple regression and logistic regression in R
josephmachado/beginner_de_project
Beginner data engineering project - batch edition
dmkarthiksrini/awesome-nlp
:book: A curated list of resources dedicated to Natural Language Processing (NLP)
dmkarthiksrini/Data_Engineering
Projects related Data Engineering Zoomcamp hosted by @DataTalksClub
dmkarthiksrini/Distributed_Data_Analysis
The goal of the project is to gain understanding and value from analysing disparate data sets. We will put into practise a number of different analytic methods, techniques, and algorithms, assess their performance, and then compare them to one another. Teamwork and regular meetings will aid in the planning and execution of the data analysis.
sindresorhus/awesome
😎 Awesome lists about all kinds of interesting topics
keon/awesome-nlp
:book: A curated list of resources dedicated to Natural Language Processing (NLP)
dmkarthiksrini/awesome-public-datasets
A topic-centric list of HQ open datasets.
vscode-icons/vscode-icons
Icons for Visual Studio Code
jonathandinu/data-science-fundamentals-archive
This repository contains the exercises and slides for Data Science Fundamentals Live Lessons
ziritrion/dataeng-zoomcamp
Avik-Jain/100-Days-Of-ML-Code
100 Days of ML Coding
igorbarinov/awesome-data-engineering
A curated list of data engineering tools for software developers
hnasr/javascript_playground
Javascript playground tutorials
gopinav/Learning-Path-Resources
PDFs related to the Learning Path videos from YouTube