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1
Introduction
2
Agenda
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Did You Know
4
Purpose
5
dynamism
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library
7
skills needed
8
what is machine learning
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Supervised learning
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Regression
11
Unsupervised Learning
12
Clustering
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Reinforcement Learning
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Question
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Practical Demonstration
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Example
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Crime Rate
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Data Structures
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Preprocessing Data
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Assess
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Model Fitting
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Error Rate
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KNearest Neighbor
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KNearest Neighbor Example
Description:
Explore Python for machine learning in this comprehensive tutorial. Learn essential libraries like NumPy for numerical computation, Pandas for data manipulation, and Seaborn for visualization. Dive into supervised, unsupervised, and reinforcement learning concepts. Follow along with practical demonstrations, including a crime rate prediction example using data preprocessing, model fitting, and k-nearest neighbor algorithm. Gain valuable skills for implementing machine learning tasks and advance your career in data science and artificial intelligence.

Python for Machine Learning - Machine Learning Tutorial - Python Tutorial

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