ML with Python: A Practical Introduction
Learn the fundamental techniques of supervised and unsupervised learning and apply them to real-world problems to unlock the potential of machine learning.
statistical modeling,random forest algorithm,python,machine learning,algorithms,unsupervised learning
Description for ML with Python: A Practical Introduction
Supervised Learning Algorithms: Acquire knowledge regarding supervised learning algorithms, which encompass classification and regression methodologies.
Unsupervised Learning Algorithms: Comprehend unsupervised learning algorithms, including dimensionality reduction and clustering techniques.
Statistical Modeling and Machine Learning: Investigate the correlation between statistical modeling and machine learning and the methods for comparing the two.
Real-World Applications: Evaluate the societal implications of machine learning and provide examples from the real world.
Level: Beginner
Certification Degree: Yes
Languages the Course is Available: 1
Offered by: On edX provided by IBM
Duration: 4-6 hours per week approx 5 weeks
Schedule: Flexible
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