BCA 504 (C) : Machine Learning
BCA 504 (C) : Machine Learning

BCA 504 (C) : Machine Learning

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Publisher: Prime Publishing House
ISBN: 9789395605-915
Year: 2024
Pages: 68

Machine Learning is a comprehensive and beginner-friendly guide that introduces students to the core concepts and practical applications of one of the most transformative fields in computer science. The book provides a strong foundation in machine learning fundamentals, including supervised and unsupervised learning techniques, data preprocessing, and model development. It also explores essential algorithms such as regression, classification, clustering, K-Nearest Neighbour, Support Vector Machines, and Naïve Bayes.

With a focus on real-world problem-solving, the book highlights applications like spam detection, image recognition, and demand forecasting, helping students understand how machine learning is applied across industries. Written in a simple and structured manner, this book equips learners with analytical thinking, technical skills, and a practical understanding of machine learning, making it an ideal resource for students aspiring to build careers in artificial intelligence and data science.

1. Introduction to Machine Learning
1.1 What is Machine Learning?
1.2 History of Machine Learning
1.3 Need of Machine Learning
1.4 Features of Machine learning
1.5 Applications of Machine learning
1.6 Types of Machine Learning
1.7 Examples of Machine Learning

2. Datasets in Machine Learning
2.1 What is a dataset?
2.2 Types of data in datasets
2.3 Need of Dataset
2.4 Machine learning Life cycle
2.5 Data Pre-processing
2.6 Difference between Artificial intelligence and Machine learning
2.7 Basics of neural network

3. Learning with Regression
3.1 What is Regression
3.2 Use Regression Analysis
3.3 Types of Regression
3.4 Linear Regression in Machine Learning
3.5 Multiple Linear regression?

4. Introduction to Algorithm
4.1 Classification of Algorithm
4.2 What is clustering?
4.3 Types of clustering
4.4 Introduction to logistic regression in Machine Learning

5. Learning with Algorithm
5.1 K-Nearest Neighbour (KNN) Algorithm for Machine Learning
5.2 Support Vector Machine Algorithm
5.3 Naïve Bayes Classifier Algorithm

6. Define a Problem in Machine Learning
6.1 Problem Definition Framework
6.2 Steps for problem solving
6.3 Problem in machine learning
6.4 Real-World Problems (Identifying Spam, Image & Video Recognition, demand Forecasting, Virtual Personal Assistant)

BCA-504 (C) | Semester V BACHELOR OF COMPUTER APPLICATIONS (BCA) As per U.G.C. guidelines and also on the basis of the revised syllabus of Kaviyatri Bahinabai Chaudhary North Maharashtra University with effect from Academic Year 2024-25. Also useful for all Universities.

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Example product title
Rs. 68.00
Rs. 75.00
Rs. 68.00
(-9%)
Example product title
Rs. 68.00
Rs. 75.00
Rs. 68.00
(-9%)
Example product title
Rs. 68.00
Rs. 75.00
Rs. 68.00
(-9%)
Example product title
Rs. 68.00
Rs. 75.00
Rs. 68.00
(-9%)
Example product title
Rs. 68.00
Rs. 75.00
Rs. 68.00
(-9%)
Example product title
Rs. 68.00
Rs. 75.00
Rs. 68.00
(-9%)
Example product title
Rs. 68.00
Rs. 75.00
Rs. 68.00
(-9%)
Example product title
Rs. 68.00
Rs. 75.00
Rs. 68.00
(-9%)
Example product title
Rs. 68.00
Rs. 75.00
Rs. 68.00
(-9%)
Example product title
Rs. 68.00
Rs. 75.00
Rs. 68.00
(-9%)

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