Computer Science

ML with Python: A Practical Introduction

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Learn the fundamental techniques of supervised and unsupervised learning and apply them to real-world problems to unlock the potential of machine learning.

Key AI Functions:

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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