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 What is numpy? NumPy is an open source project that enables numerical computing with Python. Numpy is implemented in C, its performance is faster than a Python list. Document Core Features ndarray : N-dimensional Array Object, the basic data type of NumPy. Vectorization : Operations (or Calculations) performed on the entire array without explicit loops. Broadcasting : Enables operations between arrays of different shapes (or sizes) Array Operations and Attributes 1. Array Creation np.array(): Creates an array from a Python list. np.zeros(): An array filled with zeros. np.ones(): An array filled with ones. np.arange(): An array of consecutive numbers. np.linspace(): An array with evenly spaced numbers. np.random: Module for generating random arrays. 2. Array Attributes shape: The array's dimensions/axes (rows, columns). dtype: Data type. ndim: Number of dimensions. size: Total number of elements. 3. Array Indexing and Slicing Basic Indexing: arr[0], arr[1, 2] Slicing: arr[1:3]...

Week 1. Intro to Machine Learning Machine Learning Definition A process of extracting patterns from data An algorithm that learns patterns from data and predicts outcomes. Related concepts Model:  The output of a machine learning algorithm after it has been trained on data. A model encapsulates all the patterns learned during training. Model Training 2 Types of Data - feature: all information about the object - target: What we want to predict about the project Comparison: Rule-Based Systems VS Machine Learning Example: Spam Mail Case 1. Rule-Base System Observing data and create rules to filter spam mail ex) if a mail contains ‘review, promotion, …’ then this mail is a spam -> but spams are keep changing…. it is hard to maintain the code and add new rules… JUST USE MACHINE LEARNING! Case 2. Machine Learning Get Data Define & Calculate features Train and use the model - in this case, use model to classify messages into spam or not spam Process of ML Features: We put t...