What you’ll learn in Python for Data Science and Machine Learning Bootcamp
- Python is a programming language that can be used to perform data science and machine learning.
- Spark is a programming language that can be used to analyze large amounts of information.
- Machine Learning Algorithms should be implemented.
- NumPy for Numerical Data is a Python package that you can learn how to use.
- Discover how to analyze data with Pandas.
- For Python plotting, learn how to use Matplotlib.
- For statistical plots, learn to use Seaborn.
- Plotly is a program that allows you to create dynamic interactive visualizations.
- Machine Learning Tasks with SciKit-Learn
- Clustering by the K-Means method
- Logistic regression is a statistical technique for predicting the outcome of
- Regression with a Line
- Decision Trees and Random Forests
- Filters for spam and natural language processing
- Nervous Systems
- Machines that provide support
- experience with programming
- To download files, you must have administrative permissions.
Are you prepared to begin your career as a Data Scientist?
This comprehensive course will teach you how to use Python’s power to analyze data, create stunning visualizations, and apply powerful machine learning algorithms!
According to Indeed, a data scientist’s average salary in the United States is over $120,000! Data Science is a rewarding career that allows you to solve some of the world’s most interesting problems!
This comprehensive course is comparable to other Data Science bootcamps that typically cost thousands of dollars, but you can now learn all of that information for a fraction of the price! With over 100 HD video lectures and detailed code notebooks for each lecture, this is one of the most comprehensive data science and machine learning courses on Udemy!
Who this course is for:
- This course is meant for people with at least some programming experience
|File Name :||Python for Data Science and Machine Learning Bootcamp Free Download|
|Genre / Category:||Data Science|
|File Size :||14.20 gb|
|Publisher :||Jose Portilla|
|Updated and Published:||24 Oct,2021|