Nov

20

2021

Build 30 Real Data Science Projects With Python Practically

Laser 20 Nov 2021 19:26 LEARNING » e-learning - Tutorial

Build 30 Real Data Science Projects With Python Practically
Last Update: 11/2021Duration: 19h 29m | Video: .MP4, 1280x720 30 fps | Audio: AAC, 44.1 kHz, 2ch | Size: 10.8 GBGenre: eLearning | Language: English

Practical Data Science Course: Learn To Build Machine Learning, Data Science Projects & Case Studies With Python
What you'll learn:
Learn how to build data science models
Build Best Perfog Machine Learning Models
Have a great intuition of many data science models
Make robust data science models
Create supervised machine learning algorithms to predict classes.

Learn how to use Scikit-learn to apply powerful machine learning algorithms.
Learn best practices for real-world data sets.
How to improve your Machine Learning Models
Description:
Machine learning is a very promising subfield of artificial intelligence, where systems have the ability to "learn" through data, statistics and trial and error in order to optimize processes and innovate at quicker rates. Machine learning is giving computers the ability to develop human-like learning capabilities that are allowing them to solve some of the world's toughest problems, rag from cancer research to climate change.
How, exactly, is machine learning making computers more human-like Most computer programs rely on code to tell them what to execute or what information to retain (better known as explicit knowledge). This knowledge contains anything that is easily written or recorded, like textbooks, videos or manuals. With machine learning, computers are now gaining tacit knowledge, or the knowledge we gain from personal experience and context. This type of knowledge is hard to transfer from one person to the next via written or verbal communication.
For example, facial recognition is a type of tacit knowledge. We recognize a person's face, but it is hard for us to accurately describe how or why we recognize it. We rely on our personal knowledge banks to tacitly connect the dots to immediately recognize a person based on their face. Another example is riding a bike. It's much easier to show someone how to ride a bike than it is to explain it.
Computers no longer have to rely on billions of lines of code to carry out calculations. Machine learning gives computers the power of tacit knowledge that allows these machines to make connections, discover patterns and make predictions based on what it learned in the past. Machine learning's use of tacit knowledge has made it a go-to technology for almost every industry from fintech to weather and government.
Who this course is for:
Bners in data science




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