Shivaam Sanatan - Invidious

Shivaam Sanatan

You'll discover daily videos offering valuable insights, tips, and tricks related to the latest technology and Important learning, Data Science Course all presented in Hindi and Regional Language. My goal is to provide you with clear and concise guidance to help you stay ahead in the ever-evolving world of technology.

If you have any questions or would like to explore a specific topic further, feel free to leave a comment. I'm committed to addressing your queries and will strive to create videos that answer your questions and meet your informational needs.

If you find the content on this channel informative and engaging, I invite you to subscribe and like the videos. Your support is truly appreciated!

Jai Hind 🇮🇳

For Business inquiry - realshivamsanatan@gmail.com

Thanks
Shivam Sanatan
#shorts #shortvideo #viral #shivamsanatan
😊

View channel on YouTube

Switch Invidious Instance

Videos

Shorts

Livestreams

Courses

Playlists

Posts

Shivaam Sanatan

What is the Data Science Lifecycle?

The Data Science Lifecycle is the process data scientists follow to complete a data science project.

It consists of several stages:

Problem Definition: Clearly define the problem you want to solve and understand the objectives.

Data Collection: Gather relevant data from various sources, such as databases, APIs, or external datasets.

Data Preparation: Clean, organize, and preprocess the data to ensure it's ready for analysis. This includes handling missing values, removing duplicates, and formatting data correctly.

Exploratory Data Analysis (EDA): Analyze the data to identify patterns, trends, and relationships. Use visualization tools to gain insights.

Model Building: Develop and train machine learning models or statistical algorithms to solve the problem.

Model Evaluation: Test the model's performance using metrics like accuracy, precision, recall, or F1 score to ensure it meets the objectives.

Deployment: Integrate the model into production systems so it can be used in real-world applications.

Monitoring and Maintenance: Continuously monitor the model's performance and update it as needed to adapt to new data or changing requirements.

With these steps, data scientists ensure that they cover all the basics when working on a project, from ideation to production release.

3 weeks ago | [YT] | 1

View 0 replies

Shivaam Sanatan

“जननी जन्मभूमिश्च स्वर्गादपि गरीयसी”
Mother and motherland are greater than heaven. 🙏❤🇮🇳