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The COM6018 module book

Course Notes

000 COM6018 Course Notes
005 Getting Started
010 Getting Started with Python
015 Further Python
020 Reading and Writing Data Files
025 Obtaining Data via an API
030 Numerical Computing with NumPy
035 Some Common Problems
040 Processing Data with Pandas
045 Common Pandas Mistakes
050 Exploratory Data Analysis and Visualisation
070 Introducing Scikit-Learn
080 Classification with scikit-learn
090 Curve Fitting with scikit-learn
100 Evaluating Classifier Performance
110 Further scikit-learn pipelines

Lectures

000 COM6018 Lecture Notes
005 Getting Started
010 Welcome to COM6018
015 Getting set up
020 Reading and Writing Data
030 Introducing NumPy
040 Introducing Pandas
050 Data Visualisation with Matplotlib and Seaborn
070 An Introduction to Scikit-Learn
080 Classification with Scikit-Learn
090 Curve Fitting with Scikit-Learn
100 Evaluating Classifiers
105 More Assignment Feedback
110 Further scikit-learn Pipelines

Lab Introductions

000 COM6018 Lab Introductions
010 Introduction to Lab 1
020 Introduction to Lab 2
030 Introduction to Lab 3
040 Introduction to Lab 4
050 Introduction to Lab 5
070 Introduction to Lab 7
080 Introduction to Lab 8
090 Introduction to Lab 9
100 Introduction to Lab 10

Lab Classes

000 COM6018 Lab Classes
010 Getting Started with Python
020 Reading data
030 Introducing NumPy
040 Working with Pandas
050 Using Matplotlib
070 Introduction to Scikit-learn
080 Classification with scikit-learn
090 Curve Fitting with scikit-learn
100 Evaluating Classifiers

Solutions

000 COM6018 Solutions
010 Getting Started with Python
020 Reading data
030 Introducing NumPy
040 Working with Pandas
050 Using Matplotlib
070 Introduction to Scikit-learn
080 Classification with scikit-learn
090 Curve Fitting with scikit-learn

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110 Further scikit-learn Pipelines

110 Further scikit-learn Pipelines#

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110 Further scikit-learn Pipelines

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000 COM6018 Lab Introductions

By Jon Barker, University of Sheffield

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