Name: Introduction to Machine Learning (Basic Concepts & Applications)
Brand: Prolander Tech.
SKU: 67de8aa29773dd34ce0f89a3
Price: 999 INR
Availability: InStock

Introduction to Machine Learning (Basic Concepts & Applications)

"Unlock the Power of Machine Learning: Build Smart Models & Make Data-Driven Decisions!" 🚀

Instructor: pedagogy trainings

Language: English

Validity Period: 90 days

₹1499 33% OFF

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	Module 1: Introduction to Machine Learning (1 Hour)
		What is Machine Learning?
		Types of Machine Learning: Supervised, Unsupervised, and Reinforcement Learning
		Self Check Quiz 1
		Real-world applications of ML
	Module 2: Essential Machine Learning Workflow (1 Hour)
		Data collection and preprocessing
		Feature selection and engineering
		Model building and evaluation
	Module 3: Understanding Supervised Learning (2 Hours)
		Regression vs. Classification
		Introduction to Linear Regression
		Introduction to Decision Trees and Random Forest
		Hands-on practice with basic supervised learning models
	Module 4: Introduction to Unsupervised Learning (2 Hours)
		Clustering techniques (K-Means, Hierarchical Clustering)
		Dimensionality Reduction (PCA overview)
		Hands-on with simple unsupervised learning models
	Module 5: Model Evaluation and Performance Metrics (2 Hours)
		Accuracy, Precision, Recall, and F1-score
		Confusion Matrix for classification models
		Mean Squared Error for regression models
		Cross-validation techniques
	Module 6: Introduction to Neural Networks & Deep Learning (1 Hour)
		Basics of Neural Networks
		Difference between ML and Deep Learning
		Simple neural network architecture overview
	Module 7: Applications and Industry Use Cases (1 Hour)
		ML in Finance, Healthcare, and E-commerce
		Recommendation Systems
		Fraud Detection and Predictive Analytics
	Module 8: Hands-on Mini Project (2 Hours)
		Implementing a basic ML model on real-world data
		Training and evaluating a model using Python
		Interpreting results and insights

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Introduction to Machine Learning (Basic Concepts & Applications)

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