Learnt DOM in js from Chai and Code
Learnt DATA SCIENCE LIFECYCLE from CWH DS course
Problem Definition - the first step is to understand the problem what exactly what do you want to solve
Data Collection - it is the process of collecting data from various sources such as Web Scraping, Databases, Third Party Data, APIs etc
Data Cleaning - it is the process of cleaning data by removing or editing the inaccurate or incomplete data using various python libraries such as pandas numpy ( in the initial state data is known as data dump ) a data scientist spends around 80% of his time in data cleaning
Data Exploration - understanding the data and finding the relations and patterns in the data using Matplotlib, Seaborn
Model building - Creating and training the model for predictions or decision making the models can be a simple python program to a complex machine learning model eg : Scikit learn , Tensor flow, PyTorch
Model Evaluation - it is the process of checking how accurate the model is , it is done by using some data for evaluation and some data for training the model
Deployment - grounding the model in to the real world or the production system using Flask, Fast API, React
Communication and reporting - sharing insights at the end of the day
Maintenance and Evaluation - Keeping the model updated and accurate as the inaccurate data may lead to inconsistency in the result
Top comments (1)
Good job myself keep going 👍