It is a Natural Language Processing Problem where Sentiment Analysis is done by Classifying the Positive tweets from negative tweets by machine learning models for classification, text mining, text analysis, data analysis and data visualization
Amora Data Build Tool enables analysts and engineers to transform data on the data warehouse (BigQuery) by writing Amora Models that describe the data schema using Python's "PEP484 - Type Hints" and select statements with SQLAlchemy. Amora is able to transform Python code into SQL data transformation jobs that run inside the warehouse.
This repo contains 4 different projects. Built various machine learning models for Kaggle competitions. Also carried out Exploratory Data Analysis, Data Cleaning, Data Visualization, Data Munging, Feature Selection etc
⚒️ Data preprocessing is the process of transforming raw data into an understandable format. It is also an important step in data mining as we cannot work with raw data. The quality of the data should be checked before applying machine learning or data mining algorithms
A basic machine learning model built in python jupyter notebook to classify whether a set of tweets into two categories: racist/sexist non-racist/sexist.