Description
Fantastic Python: Data Science and Machine Learning Course. This course in the Fantastic Python series is a complete guide to Python coding and machine learning for beginners and intermediate programmers. You will not only learn Python, but also how to do data analysis, data visualization, and machine learning (ML) using Pandas, Numpy, Scikit-Learn, Statsmodels, Seaborn, and more. Practical examples of ML include: (1) handwritten digit classification; (2) face recognition; (3) heart disease prediction; (4) penguin classification; (5) global happiness index; and many more. Specifically, this course consists of 3 main parts (“mini-courses”):
- Python coding training
- All essential data types and common operations
- Manipulation of large strings
- flow control
- Lists, tuples and collections
- Dictionaries
- objective programming
- estate
- meeting
- Modules and packages
- Exception handling, etc.
- Learn data analysis and visualization with Pandas and Seaborn
- Data series and frames
- Indexing, filtering, sorting, counting, etc.
- Merger/Consolidation
- Assembly
- Line charts
- Load pieces
- Isolated conspiracies
- Histogram etc.
- Learn Machine Learning with Scikit-Learn
- linear regressions
- Logistic regressions
- Linear diagnostic analysis
- Principal component analysis
- K-agent
- K-nearest neighbors
- Support vector machines
- Neural Networks
- Decision trees
- random forests
- Set metaparameters
This course is one of the most comprehensive and detailed courses to date in the Pandas package. It highlights the complexity of data processing, which consumes about 80% of data scientists’ time, and gives you a solid foundation to meet the demanding needs of managing messy data in the real world. Machine Learning (ML) focuses on practical applications and gaining an intuitive understanding of algorithms rather than delving into theories and mathematics. By the end of this course, you will not only be a competent Python programmer, but also a budding data scientist ready to face real-world challenges.
What you will learn in the Fantastic Python: Data Science & Machine Learning course
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Data manipulation with Pandas
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Data visualization with Seaborn and Pandas
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Applications in finance, real estate, image recognition and much more
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Linear diagnostic analysis
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Principal Component Analysis (PCA)
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K-Nearest Neighbors Algorithm
This course is suitable for people who
- Beginner
- Advanced Python programmers who want to improve their machine learning skills
- All aspiring data scientists, data analysts and data engineers
- Professionals/students of other disciplines (business, marketing, finance, accounting, medicine, law, etc.)
- Anyone interested in Python and/or machine learning
Details of the Amazing Python: Data Science and Machine Learning course.
- Editor: Udemy
- Lecturer: Richard Wang
- Training level: beginner to advanced
- Training duration: 42 hours and 53 minutes
- Number of courses: 311
Course topics on 10/2023
Prerequisites for the course “Fantastic Python: Data Science & Machine Learning”.
- No programming knowledge is required. This course will teach you everything you need to know about Python, data analysis, and machine learning.
Pictures from the course “Awesome Python: Data Science and Machine Learning”.
Sample video of the course
installation Guide
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Download link
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Size
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