Introduction To Machine Learning - Jayydeep

  Aim 1: Explore any one Machine Learning tool (Scikit-learn) Program # Exploring Scikit-learn library import sklearn print ( "Scikit-learn version:" , sklearn.__version__) print ( "Scikit-learn is used for machine learning tasks such as:" ) print ( "Classification, Regression, Clustering, and Model Evaluation" ) Aim 2: NumPy basic operations Program import numpy as np # Convert list to 1D NumPy array list1 = [ 1 , 2 , 3 , 4 , 5 ] arr1 = np.array(list1) print ( "1D Array:" , arr1) # Create 3x3 matrix from 2 to 10 matrix = np.arange( 2 , 11 ).reshape( 3 , 3 ) print ( "3x3 Matrix:\n" , matrix) # Append values to array arr2 = np.append(arr1, [ 6 , 7 ]) print ( "Appended Array:" , arr2) # Reshape array from 3x2 to 2x3 arr3 = np.array([[ 1 , 2 ], [ 3 , 4 ], [ 5 , 6 ]]) reshaped = arr3.reshape( 2 , 3 ) print ( "Reshaped Array:\n" , reshaped) Aim 3: NumPy mathematical operations Program import numpy ...

  CHAPTER 1 INTRODUCTION TO MACHINE LEARNING** 1.1 Overview of Human Learning and Machine Learning Human Learning Human learning is a natural process where people gain knowledge from experience, observation, practice, and reasoning . For example: A child learns to recognize animals by seeing pictures. A driver learns to drive better with practice. Humans learn using the brain , emotions, and thinking abilities. Machine Learning Machine Learning (ML) is a branch of Artificial Intelligence (AI) that enables machines (computers) to learn from data and improve performance without being explicitly programmed . Example: Email spam filters learn from past emails. Recommendation systems suggest movies based on user behavior. 👉 Key Difference Human Learning Machine Learning Uses brain Uses algorithms Learns from experience Learns from data Emotional & logical Mathematical & statistical 1.2 Types of Machine Learning Machine Learning can be classified in...