09-16-2024, 12:05 PM
[center]![[Image: 56770d30feca1f9c7f97af7e2232f264.png]](https://i124.fastpic.org/big/2024/0915/64/56770d30feca1f9c7f97af7e2232f264.png)
Machine Learning In 9 Days Beginner To Advance Using Python
Published 9/2024
Created by Mallika Srivastava
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 24 Lectures ( 8h 29m ) | Size: 3.21 GB
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Learn to understand NumPy, Pandas, Matplotlib, Sklearn, model deployment, forecasting, prediction through ML models
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What you'll learn:
Learn Machine Learning from beginner to advance level
Explain all the concepts theoretically as well as practically
First we brush up Python and then start the concept of Machine Learning
Create multiple ML projects
Explain the statistical part in easiest way
Define data analytics, arrays, data visualizations and many more...
Create multiple ML models and understand the usage
All the notes are available in recourses
Requirements:
Beginner level of Python required
Helpful if you have any programming background
Explain each and every line very clearly so if you are beginner then also do not worry
Description:
In this course I am going to describe what is exactly Machine Learning, I will explain different types of Machine Learning with real world examples so you understands the concepts easily. Then I start with NumPy which we use to make arrays in python and that too with different dimensions of array. we together apply multiple operations on arrays, try to access desired information/data from the array and then multiple operations on array. Also we then try to figure out how NumPy array is better than Python list in case of machine Learning.After that we start working on Pandas library of Python to start working on different datasets. we understand types of pandas data type like series, DataFrame and panels and we store our data in data frames and apply different operations on DataFrame. We will try to handle missing values, data normalization, One hot encoding and much more.Then we start doing data visualization using Matplotlib library of Python which is very interesting, and by using it we are able to gather hidden insights of datasets.Then we start working on different project of Machine Learning for future prediction and concepts of forecasting.And at the end we will try to deploy our model on a webpage so anyone can use that ML model by abstracting the code.
Who this course is for:
This course is for the person who want to start exploring Machine Learning field
Beginner Python developers who wants to explore data
Homepage
Machine Learning In 9 Days Beginner To Advance Using Python
Published 9/2024
Created by Mallika Srivastava
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 24 Lectures ( 8h 29m ) | Size: 3.21 GB
[/center]
[center]
Learn to understand NumPy, Pandas, Matplotlib, Sklearn, model deployment, forecasting, prediction through ML models
[/center]
What you'll learn:
Learn Machine Learning from beginner to advance level
Explain all the concepts theoretically as well as practically
First we brush up Python and then start the concept of Machine Learning
Create multiple ML projects
Explain the statistical part in easiest way
Define data analytics, arrays, data visualizations and many more...
Create multiple ML models and understand the usage
All the notes are available in recourses
Requirements:
Beginner level of Python required
Helpful if you have any programming background
Explain each and every line very clearly so if you are beginner then also do not worry
Description:
In this course I am going to describe what is exactly Machine Learning, I will explain different types of Machine Learning with real world examples so you understands the concepts easily. Then I start with NumPy which we use to make arrays in python and that too with different dimensions of array. we together apply multiple operations on arrays, try to access desired information/data from the array and then multiple operations on array. Also we then try to figure out how NumPy array is better than Python list in case of machine Learning.After that we start working on Pandas library of Python to start working on different datasets. we understand types of pandas data type like series, DataFrame and panels and we store our data in data frames and apply different operations on DataFrame. We will try to handle missing values, data normalization, One hot encoding and much more.Then we start doing data visualization using Matplotlib library of Python which is very interesting, and by using it we are able to gather hidden insights of datasets.Then we start working on different project of Machine Learning for future prediction and concepts of forecasting.And at the end we will try to deploy our model on a webpage so anyone can use that ML model by abstracting the code.
Who this course is for:
This course is for the person who want to start exploring Machine Learning field
Beginner Python developers who wants to explore data
Homepage
Code:
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