[ FreeCourseWeb.com ] Udemy - Python for Machine Learning bootcamp
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Video: .MP4, 1280x720 30 fps | Audio: AAC, 44.1 kHz, 2ch | Duration: 19:58:34
Genre: eLearning | Language: English + Subtitles | Size: 8.03 GB
Learn to create Machine Learning Algorithms in Python from Zero to Hero
What you'll learn
Become a professional Python Developer and get hired
Master modern Python 3 fundamentals as well as advanced topics
Learn Object Oriented Programming
Learn Machine Learning with Python
Learn Function Programming
Create data visualizations using matplotlib and the seaborn modules with python.
Use the pandas module with Python to create and structure data.
Use the Jupyter Notebook Environment.
Use the numpy library to create and manipulate arrays.
Build an army of powerful Machine Learning models and know how to combine them to solve any problem
Make powerful analysis
Requirements
Have a computer (either Mac, Windows, or Linux)
No prior knowledge of Python is required.
No previous programming experience is needed.
Description
Interested in the field of Machine Learning ? Then this course is for you !
This course has been designed by two professional Data Scientists so that we can share our knowledge and help you learn complex theory, algorithms and coding libraries in a simple way.
We will walk you step-by-step into the World of Machine Learning. With every tutorial you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science.
This course is fun and exciting, but at the same time we dive deep into Machine Learning. It is structured the following way:
01 - Python basic
02 - Object-Oriented Programming
03 - Numpy
04 - Matplotlib
05 - Panda
06 - Data Visualization - Plotly and Cufflinks
07 - Data Visualization in Pandas
08 - Seaborn
09 - In troduction to Machine Learning
10 - Linear Regression
11 - Logistic Regression Titanic Dataset
12 - KNN algorithm
13 -SVM
14 - Decision Tree Classifier and Regressor
15 - Random Forest Classifier and Regressor
16 - K-Mean Clustering
17 - Principal Component Analysis (PCA)
18 - Ensemble Learning
19 - Learning Curve
20 - Python Interview Questions
Moreover, the course is packed with practical exercises which are based on real-life examples. So not only will you learn the theory, but you will also get some hands-on practice building your own models.
And as a bonus, this course includes Python code templates which you can download and use on your own projects.
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