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Python for Machine Learning Project based Master course

Python for Machine Learning Project based Master course
Python for Machine Learning Project based Master course
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 ChGenre: eLearning | Language: English + srt | Duration: 21 lectures (3h 10m) | Size: 924.7 MB

Learn Machine Learning using Python, Regression, Decision Trees, SVM, Numpy, Pandas, Scikit-Learn, Matplotlib streamlit

Use Python for Data Science and Machine Learning
Create Machine Learning projects webapp using streamlit
Learn to use Pandas for Data analysis
Implement Scikit-Learn for Machine Learning projects
Linear Regression
Learn to use Matplotlib for Python Plotting
Random Forest and Decision Trees
Support Vector Machines
Learn to use NumPy for Numerical Data

None

Are you ready to start your career in Machine learning and as a Data Scientist.

This course will be your guide to learning how to use the power of Python and the libraries to analyze data, create beautiful visualizations, and use powerful machine learning algorithms!
It is a brilliant course where you will learn how to setup the project step by step from installation of python and the libraries to finished project. There are three projects that will allow you to use and implement supervise and unsupervise learning in the projects.
You will learn to create the following projects
1. Salary Predictor
2. Classification Webapp
3. BMI Calculator
This course will allow you to utilise and implement several Machine learning libraries to these projects. The list are:
Streamlit
KNN Clustering
SVM
Numpy
Pandas
MatplotLib
Scikit-Learn
Furthermore, you will be able to assess your knowledge through doing a quiz on Streamlit and Machine Learning. Also, a challenge is set to create a BMI calculator. Solutions are given in text form and video for explanation.
So I invite you to join me, Developer Shack on an exciting journey into unlocking the secrets of Machine Learning for Data Science.
Sign up right now, and let's create amazing Machine learning apps!

Machine Learning Enthusiasts
Data Scientist Enthusiasts


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