Shubham Narkhede's repositories
Data_Science_Practice
# Data_Science_Practice Hello, In this repos you will find all the implementations I do in the process of becoming a Data Scientist.
500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code
500 AI Machine learning Deep learning Computer vision NLP Projects with code
project-based-learning
Curated list of project-based tutorials
free-for-dev
A list of SaaS, PaaS and IaaS offerings that have free tiers of interest to devops and infradev
DSA-Cracker
Practice DSA with curated coding questions & resources.
Youtube_Video_Stance_Aanalysis
Web Mining Project
Python_for_Financial_Applications
FE-520 Course
100-Days-Of-ML-Code
100 Days of ML Coding
Coursera_Capstone
Applied Data Science Capstone Project
Notes-App
Building a Notes Taking Web-App using Restful CRUD API with Node.js, Express and MongoDB
developers-guide
Resources for developers to access
hacktoberfest-2021
Let's change the world together with Open-Source & tackle Climate-Change
Learning-Data-Science
Using Online resources to learn from complete basics
ANZ-Data-Analysis-Internship
Data analysis of customer data .
CtCI-6th-Edition
Cracking the Coding Interview 6th Ed. Solutions
gitintro
Coursera course
LSTM-Neural-Network-for-Time-Series-Prediction
LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data
A-Novel-Approach-for-Network-Intrusion-Detection-using-Probability-parameter-to-ensemble-Machine-Lea
I WILL RELEASE THE CODE AFTER MY PAPER IS PUBLISHED.Aim of this project is to develop an algorithm which has better performance than the existing methods.This project is basically detecting any unauthorised intruder in the network.This intruder can be through DDOS, Probe attack, U2R ,R2L attacks,etc.NSL-KDD and CIC-NID-2017 datasets have been used for training the models.
50-Days-of-ML
A day to day plan for this challenge (50 Days of Machine Learning) . Covers both theoretical and practical aspects
How-to-Predict-Stock-Prices-Easily-Demo
How to Predict Stock Prices Easily - Intro to Deep Learning #7 by Siraj Raval on Youtube
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.
Learn_Data_Science_in_3_Months
This is the Curriculum for "Learn Data Science in 3 Months" By Siraj Raval on Youtube