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Cut through the noise and get real results with a step-by-step
approach to understanding supervised learning algorithms Key
Features Ideal for those getting started with machine learning for
the first time A step-by-step machine learning tutorial with
exercises and activities that help build key skills Structured to
let you progress at your own pace, on your own terms Use your
physical print copy to redeem free access to the online interactive
edition Book DescriptionYou already know you want to understand
supervised learning, and a smarter way to do that is to learn by
doing. The Supervised Learning Workshop focuses on building up your
practical skills so that you can deploy and build solutions that
leverage key supervised learning algorithms. You'll learn from real
examples that lead to real results. Throughout The Supervised
Learning Workshop, you'll take an engaging step-by-step approach to
understand supervised learning. You won't have to sit through any
unnecessary theory. If you're short on time you can jump into a
single exercise each day or spend an entire weekend learning how to
predict future values with auto regressors. It's your choice.
Learning on your terms, you'll build up and reinforce key skills in
a way that feels rewarding. Every physical print copy of The
Supervised Learning Workshop unlocks access to the interactive
edition. With videos detailing all exercises and activities, you'll
always have a guided solution. You can also benchmark yourself
against assessments, track progress, and receive content updates.
You'll even earn a secure credential that you can share and verify
online upon completion. It's a premium learning experience that's
included with your printed copy. To redeem, follow the instructions
located at the start of your book. Fast-paced and direct, The
Supervised Learning Workshop is the ideal companion for those with
some Python background who are getting started with machine
learning. You'll learn how to apply key algorithms like a data
scientist, learning along the way. This process means that you'll
find that your new skills stick, embedded as best practice. A solid
foundation for the years ahead. What you will learn Get to grips
with the fundamental of supervised learning algorithms Discover how
to use Python libraries for supervised learning Learn how to load a
dataset in pandas for testing Use different types of plots to
visually represent the data Distinguish between regression and
classification problems Learn how to perform classification using
K-NN and decision trees Who this book is forOur goal at Packt is to
help you be successful, in whatever it is you choose to do. The
Supervised Learning Workshop is ideal for those with a Python
background, who are just starting out with machine learning. Pick
up a Workshop today, and let Packt help you develop skills that
stick with you for life.
Explore the exciting world of machine learning with the fastest
growing technology in the world Key Features Understand various
machine learning concepts with real-world examples Implement a
supervised machine learning pipeline from data ingestion to
validation Gain insights into how you can use machine learning in
everyday life Book DescriptionMachine learning-the ability of a
machine to give right answers based on input data-has
revolutionized the way we do business. Applied Supervised Learning
with Python provides a rich understanding of how you can apply
machine learning techniques in your data science projects using
Python. You'll explore Jupyter Notebooks, the technology used
commonly in academic and commercial circles with in-line code
running support. With the help of fun examples, you'll gain
experience working on the Python machine learning toolkit-from
performing basic data cleaning and processing to working with a
range of regression and classification algorithms. Once you've
grasped the basics, you'll learn how to build and train your own
models using advanced techniques such as decision trees, ensemble
modeling, validation, and error metrics. You'll also learn data
visualization techniques using powerful Python libraries such as
Matplotlib and Seaborn. This book also covers ensemble modeling and
random forest classifiers along with other methods for combining
results from multiple models, and concludes by delving into
cross-validation to test your algorithm and check how well the
model works on unseen data. By the end of this book, you'll be
equipped to not only work with machine learning algorithms, but
also be able to create some of your own! What you will learn
Understand the concept of supervised learning and its applications
Implement common supervised learning algorithms using machine
learning Python libraries Validate models using the k-fold
technique Build your models with decision trees to get results
effortlessly Use ensemble modeling techniques to improve the
performance of your model Apply a variety of metrics to compare
machine learning models Who this book is forApplied Supervised
Learning with Python is for you if you want to gain a solid
understanding of machine learning using Python. It'll help if you
to have some experience in any functional or object-oriented
language and a basic understanding of Python libraries and
expressions, such as arrays and dictionaries.
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