Fundamental of MLAIML 210, AIDS 210

About the work

• We give you the syllabus below and a sample notes PDF to record from. The notes unlock once you fill in your details in the form.
• You send back a link to an unlisted YouTube video or a Drive video of yourself teaching from those notes. Nothing to upload here.
• Selected educators have 3-4 weeks to submit the full recording.
• Payment for the subject: Upto 1500-2000 (Based on Hrs of recording).
• Shortlisted applicants are contacted by our team with the next steps.

Subject syllabus

Exactly what you would be recording.

UNIT I:
Introduction to Machine Learning- Basic concepts, developing a learning system, Learning Issues, and challenges. Types of Machine Learning. Feature Selection Mechanisms, Imbalanced Data, Bias in Data, Outlier Detection
UNIT II:
Supervised Learning- Linear Regression, Multiple Regression, Logistic Regression, Classification; Classifier Models, K Nearest Neighbor (KNN), Naive Bayes, Decision Trees, Support Vector Machine (SVM), Random Forest
UNIT III:
Unsupervised Learning- Dimensionality Reduction; Clustering; K-Means Clustering; C-Means Clustering; Fuzzy C Means Clustering, Association Analysis- Association Rules in Large Databases, Apriori Algorithm, Markov Models: Hidden Markov Models (HMMs).
UNIT IV:
Reinforcement Learning- Introduction to Reinforcement Learning, Elements of Reinforcement Learning, Approaches to Reinforcement Learning, Applications of Reinforcement learning. Applications of Machine Learning in different sectors: Medical Diagnostics, Fraud Detection, Email Spam Detection