kashish45's Stars
ashishps1/awesome-system-design-resources
Learn System Design concepts and prepare for interviews using free resources.
sidakwalia/Data-Science-Cheat-Sheet
This repository contains all the Cheat Sheet for Data Science,Python Libraries and Git.
VSerpak/DSE210x-Statistics-and-Probability-in-Data-Science-using-Python
UCSanDiegoX edX Course DSE210x Statistics and Probability in Data Science using Python
suneelpatel/Statistics-for-Data-Science-using-Python
Using Python, learn statistical and probabilistic approaches to understand and gain insights from data. Learn statistical concepts that are very important to Data science domain and its application using Python. Learn about Numpy, Pandas Data Frame.
scaleracademy/Edge-DSML
Data Science and Machine Learning codes for Scaler Edge Batch
cerlymarco/MEDIUM_NoteBook
Repository containing notebooks of my posts on Medium
prasadgujar/low-level-design-primer
Dedicated Resources for the Low-Level System Design. Learn how to design and implement large-scale systems. Prep for the system design interview.
debadridtt/ZS-Data-Science-Challenge-2018---Airline-Tweet-Sentiment
A typical ML problem based on NLP put up by ZS Associates on Hackerearth
Abhishekmamidi123/ZS-Data-Science-Challenge
A Data science challenge - "Mekktronix Sales Forecasting" organised by ZS through Hackerearth platform. Rank: 223 out of 4743.
AmandaZou/Data-Science-books-
A repository of books in data science
krishvictor77/Time-Series-Forecasting-ARIMA-vs-Prophet
Comparison between time series forecasting models such as ARIMA, Seasonal SARIMA and Prophet
trewaite/Electricity-Demand-Forecasting--ARIMA-
4th year project
yasamanensafi/retail_store_sales_forecasting
Predict seasonal item sales using classical time-series forecasting methods like Seasonal ARIMA and Triple Exponential Smoothing and current methods such as Prophet, Long Short-Term Memory (LSTM), and Convolutional Neural Network (CNN)
veeranalytics/Forecasting-ARIMA-Python
Forecasting Sales Using ARIMA in Python
lxu213/arima-forecasting
Using Python StatsModel ARIMA to Forecast Time Series of Cars in Walmart Parking Lot
pyaf/load_forecasting
Forecasting electric power load of Delhi using ARIMA, RNN, LSTM, and GRU models
tomonori-masui/time-series-forecasting
Multi-step Time Series Forecasting with ARIMA, LightGBM, and Prophet
Housiadas/forecasting-energy-consumption-LSTM
Development of a machine learning application for IoT platform to predict electric energy consumption in smart building environment in real time.
jiwidi/time-series-forecasting-with-python
A use-case focused tutorial for time series forecasting with python
har200105/striverSDESheet
A Complete Solution of the well known 'Striver SDE Sheet ' in C++.
cartershanklin/pyspark-cheatsheet
PySpark Cheat Sheet - example code to help you learn PySpark and develop apps faster
srivatsan88/End-to-End-Time-Series
This repository hosts code for my Time Series videos part of playlist here - https://www.youtube.com/playlist?list=PL3N9eeOlCrP5cK0QRQxeJd6GrQvhAtpBK
Azure/BatchSparkScoringPredictiveMaintenance
Batch scoring Spark models on Azure Databricks: A predictive maintenance use case
boutrosrg/Predictive-Maintenance-In-PySpark
Azure/PySpark-Predictive-Maintenance
Predictive Maintenance using Pyspark
sabderra/predictive-maintenance-spark
Predicting the Remaining Useful Life (RUL) of simulated Turbofan Engines using Spark ML, Spark Structured Streaming, and Kafka.
kunal-kushwaha/DSA-Bootcamp-Java
This repository consists of the code samples, assignments, and notes for the Java data structures & algorithms + interview preparation bootcamp of WeMakeDevs.
akshaymarch7/project-ideas
Ronet05/Skill-Based-Resume-Parser
Repo to win Deloitte Hackathon 2019
meghnalohani/Resume-Scoring-using-NLP
The objective of the project is to create a Resume Scoring algorithm using Natural Language Processing. The algorithm will parse resumes one by one and will create a Candidate Profile based on the skills mentioned in the resume. A corpus is created using Sketch Engine, Wikipedia pages for various required skills (example : Machine Learning, Data Science, Software developer, Programming) are given as input, Sketch Engine creates a corpus from the useful data available on the given links. Word Embeddings are created from the corpus and these are used to match the skills in the candidate resume with the required skills. Finally, the candidate profile is built and plotted as a bar graph for better visualization.