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UDEMY COUPON - Machine Learning & Data Science in Python For Beginners
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Learn Supervised & Unsupervised ML, Machine Learning Process, Models, Python, NumPy, Pandas, Seaborn, Data Visualisation
Created by Peter Alkema
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What you'll learn
- What is Machine Learning
- Supervised Machine Learning
- Unsupervised Machine Learning
- Semi-Supervised Machine Learning
- Types of Supervised Learning: Classification
- Regression
- Types of Unsupervised Learning: Clustering
- Association
- Data Collection
- Data Preparing
- Selection of a Model
- Data Training and Evaluation
- HPT in Machine Learning
- Prediction in ML
- DPP in ML
- Need of DPP
- Steps in DPP
- Python Libraries
- Missing, Encoding, and Splitting Data in ML
- Python, Java, R,and C ++
- How to install python and anaconda?
- Interface of Jupyter Notebook
- Mathematics in Python
- Euler's Number and Variables
- Degree into Radians and Radians into Degrees in Python
- Printing Functions in Python
- Feature Scaling for ML
- How to Select Features for ML
- Filter Method
- LDA in ML
- Chi Square Method
- Forward Selection
- Training and Testing Data Set for ML
- Selection of Final Model
- ML Applications
- Practical Skills in ML: Mastery
- Process of ML
- What is Extension in ML
- ML Tradeoff
- ML Variance Error
- Logistic Regression
- Data Visualization
- Pandas and Seaborn-Library for ML
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