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Learning how to apply unsupervised algorithms on unlabeled datasets
from scratch can be easier than you thought with this beginner's
workshop, featuring interesting examples and activities Key
Features Get familiar with the ecosystem of unsupervised algorithms
Learn interesting methods to simplify large amounts of unorganized
data Tackle real-world challenges, such as estimating the
population density of a geographical area Book DescriptionDo you
find it difficult to understand how popular companies like WhatsApp
and Amazon find valuable insights from large amounts of unorganized
data? The Unsupervised Learning Workshop will give you the
confidence to deal with cluttered and unlabeled datasets, using
unsupervised algorithms in an easy and interactive manner. The book
starts by introducing the most popular clustering algorithms of
unsupervised learning. You'll find out how hierarchical clustering
differs from k-means, along with understanding how to apply DBSCAN
to highly complex and noisy data. Moving ahead, you'll use
autoencoders for efficient data encoding. As you progress, you'll
use t-SNE models to extract high-dimensional information into a
lower dimension for better visualization, in addition to working
with topic modeling for implementing natural language processing
(NLP). In later chapters, you'll find key relationships between
customers and businesses using Market Basket Analysis, before going
on to use Hotspot Analysis for estimating the population density of
an area. By the end of this book, you'll be equipped with the
skills you need to apply unsupervised algorithms on cluttered
datasets to find useful patterns and insights. What you will learn
Distinguish between hierarchical clustering and the k-means
algorithm Understand the process of finding clusters in data Grasp
interesting techniques to reduce the size of data Use autoencoders
to decode data Extract text from a large collection of documents
using topic modeling Create a bag-of-words model using the
CountVectorizer Who this book is forIf you are a data scientist who
is just getting started and want to learn how to implement machine
learning algorithms to build predictive models, then this book is
for you. To expedite the learning process, a solid understanding of
the Python programming language is recommended, as you'll be
editing classes and functions instead of creating them from
scratch.
Design clever algorithms that can uncover interesting structures
and hidden relationships in unstructured, unlabeled data Key
Features Learn how to select the most suitable Python library to
solve your problem Compare k-Nearest Neighbor (k-NN) and
non-parametric methods and decide when to use them Delve into the
applications of neural networks using real-world datasets Book
DescriptionUnsupervised learning is a useful and practical solution
in situations where labeled data is not available. Applied
Unsupervised Learning with Python guides you on the best practices
for using unsupervised learning techniques in tandem with Python
libraries and extracting meaningful information from unstructured
data. The course begins by explaining how basic clustering works to
find similar data points in a set. Once you are well versed with
the k-means algorithm and how it operates, you'll learn what
dimensionality reduction is and where to apply it. As you progress,
you'll learn various neural network techniques and how they can
improve your model. While studying the applications of unsupervised
learning, you will also understand how to mine topics that are
trending on Twitter and Facebook and build a news recommendation
engine for users. You will complete the course by challenging
yourself through various interesting activities such as performing
a Market Basket Analysis and identifying relationships between
different merchandises. By the end of this course, you will have
the skills you need to confidently build your own models using
Python. What you will learn Understand the basics and importance of
clustering Build k-means, hierarchical, and DBSCAN clustering
algorithms from scratch with built-in packages Explore
dimensionality reduction and its applications Use scikit-learn
(sklearn) to implement and analyse principal component analysis
(PCA)on the Iris dataset Employ Keras to build autoencoder models
for the CIFAR-10 dataset Apply the Apriori algorithm with machine
learning extensions (Mlxtend) to study transaction data Who this
book is forThis course is designed for developers, data scientists,
and machine learning enthusiasts who are interested in unsupervised
learning. Some familiarity with Python programming along with basic
knowledge of mathematical concepts including exponents, square
roots, means, and medians will be beneficial.
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The Variant (Paperback)
Alison R Woodward; Illustrated by Aaron Jones; Justin M Woodward
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R310
Discovery Miles 3 100
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Ships in 10 - 15 working days
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From Genesis to Revelations the Author translates the Promises of
God into Powerful, Positive, Faith-filled confessions you can speak
into your life and change your world with The Word of God.
From the Wolds of the West, across the Seas of Lorth, came the long
elf, Gyral. In wild and unfrequented realms he sought for truth and
enlightenment of the mysteries of his world, a treacherous world
infested with strange and evil life-forms, ferocious predators,
riddled with countless perils. But for Gyral, curiosity was far
more powerful than the fears that confronted him. Curiosity was his
addiction; knowledge was his quest. He had heard of the great
immortal city, the citadel of mystery and foreboding. It was the
fabulous infamous city all outsiders feared to enter. Yet the bold
wayfarer became obsessed by its existence; thus he sought to find
it. On his far journeys, he would confront all evil obstacles,
encounter the wizards of science, the wondrous characters, wild and
weird communities. He visited the inns and taverns, braved the deep
forests, and he relished the damsels. But he knew he must one day
find and behold the phenomenon, thence brazenly enter into the
citadel of Bilbabalbabul.
America home of the free and land of the brave but is this still
true? In the very near future Adam an advocate for human rights
finds himself jailed for following the first amendment. Adam finds
himself on death row staring at the world through his prison cell
because he refuses to stop teaching Christianity. Adam is heralded
as a leader and labeled public enemy number one. Armed with a pen
and a paper Adam begins to wage war against his intolerant
oppressors which places all that support him in immediate danger.
Beautiful Ugly: The Cry, The Call, The Coming is a book about
freedom and the right to exercise that freedom. Adam is willing to
die for his freedom are you willing to live for yours?
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