Introduction to Machine Learning & Python — Chapter 1: Foundations (CITP3304)

Chapter 1 of the CITP3304 course "Fundamentals of Python and Machine Learning."

This video introduces the core ideas you need before writing a single line of ML code:
what machine learning is, how it differs from traditional programming, the vocabulary
(data, features, labels, models, training, testing, evaluation), the three categories
of learning (supervised, unsupervised, reinforcement), the end-to-end workflow, why
Python is the standard for data work, and how to use machine learning responsibly.

No prior programming experience required. Designed as a foundation for the rest of
the course — NumPy, Pandas, visualization, scikit-learn, and the first ML models
(linear regression, logistic regression, KNN).

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Chapter outline
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00:00 Opening title
00:22 Why Chapter 1 matters
00:51 Summer course context
01:15 What is machine learning?
01:47 Traditional programming vs. ML
02:30 Worked example — spam detection
03:08 Why machine learning is important
03:48 Real-world applications
04:34 Vocabulary — data and dataset
05:12 Features and labels
05:49 Model, algorithm, and training
06:23 Testing, prediction, and evaluation
07:03 Classification vs. regression
07:39 Types of machine learning
08:21 Supervised learning
08:57 Unsupervised learning
09:31 The machine learning workflow
10:19 Data preparation matters
10:51 Exploratory data analysis
11:29 Why Python?
12:09 Python libraries you will use
12:42 Python working environment
13:12 Notebook workflow example
13:46 Simple student dataset example
14:25 Responsible use of machine learning
14:53 Bias and fairness
15:24 Connection to future course topics
15:55 Student success tips
16:27 Chapter 1 recap
16:58 Closing — what's next

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Reference textbook
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Lee, Wei-Meng. *Python Machine Learning*. Wiley, 2019.
ISBN: 978-1-119-54563-7
O'Reilly Learning: https://learning.oreilly.com/library/view/python-machine-learning/9781119545637/

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Course
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CITP3304 — Fundamentals of Python and Machine Learning
This video is embedded in the course Blackboard shell. Students should follow the in-course assignments, readings, and discussions alongside this material.

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Видео Introduction to Machine Learning & Python — Chapter 1: Foundations (CITP3304) канала Learning with Rodo