Whiteboard Change Management

By fazilashahidsdq | Updated: Oct. 27, 2024, 9:33 p.m.

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This video of the Data Science Life Cycle will take you through the different stages of the Data Science Life Cycle one by one in Detail with a great Example. Understanding the Data Science Life Cycle is the most crucial part while learning Data Science. Boost your career with Simplilearn's 6-months Data Science Job Guarantee Program with a placement, guarantee! Land your dream job with an average pay of 8 LPA within just 180 days of graduation or get your money back! Learn from the best and get placed in a top role by investing in yourself, risk-free - a Simplilearn promise.

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Technology
Introduction of Data Science Life cycle and the steps of data science
There are 7 steps and process of Data Science Life Cycle
Technology
Until now we describe the status quo
1: Business Understanding
Data understanding is the first step of Data science Life Cycle. In this step we understand the data. Means we can understand the problem statement. 
2. Data Collection
The second step is Data Collection. Some time data is not available so we can collect data by using crolling or scrapping
3. Data Preparation;
Data preparation is the 3rd step of data science life cycle. in this step we can clean the data ,remove missing values and also remove duplicate data

4: Data Visualization
EDA
EDA stand for exploratory analysis.This is the 4th step of data science life cycle. in this step, we can visual our data by using the graph ,charts, and line graph . we can see that our data is normalized or scattered and we can also change .
This is the 5th step and in this step we can choose right algorithm means if our problem is regression type we can use regression related algorithm are used.
5. Data Modeling
In this step we can see that our selected  algorithm  is correct or related to the problem or not. We can check the accuracy .And chechk the data in the new data .
6.Model Evaluation
7.Development Model
In this 7th step our model is ready. And we can use it.This is the last step of Data science life cycle.

Whiteboard Change Management

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