Free download udemy Machine Learning & Data Science A-Z: Hands-On Python 2021 created by Navid Shirzadi.Hurry up and download today to learn NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn, Scipy and develop Machine Learning Models in Python.
This course includes:
- 14.5 hours on-demand video
- 2 articles
- 4 downloadable resources
- Full lifetime access
- Access on mobile and TV
- Certificate of completion
What you’ll learn
- Understanding the basic concepts
- Complete tutorial about basic packages like Numpy and Pandas
- Data Visualization
- Data Preprocessing
- Understanding the concept behind the algorithms
- Developing different kinds of Machine Learning models
- Knowing how to optimize your models’ hyperparameters
- Learn how to develop models based on the requirement of your future business
Requirements
- Python’s basic syntax
Description
This course is completely categorized, and we don't start from the middle! We actually start from the concept of every term, and then we try to implement it in Python step by step.
The structure of the course is as follows:
- Chapter1: Introduction and all required installations
- Chapter2: Useful Machine Learning libraries (NumPy, Pandas & Matplotlib)
- Chapter3: Preprocessing
- Chapter4: Machine Learning Types
- Chapter5: Supervised Learning: Classification
- Chapter6: Supervised Learning: Regression
- Chapter7: Unsupervised Learning: Clustering
- Chapter8: Model Tuning
Furthermore, you learn how to work with different real
datasets and use them for developing your models. All the Python code templates
that we write during the course together are available, and you can download
them with the resource button of each section.
Remember! That this course is created for you with any background
as all the concepts will be explained from the basic! Also, the programming in
Python will be explained from the basic coding, and you just need to know the
syntax of Python.
Course content
8 sections • 74
lectures • 14h 27m total length
Instructor
He is a researcher with more than 7 years of experience in the field of controlling integrated energy systems with extensive skill in using mathematical optimization strategies.He is also proficient in coding with Python and developing machine learning and deep learning models for different applications.He has several publications in the field of designing and control strategies of energy systems using machine learning, deep learning, and artificial intelligence.
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