|
Books > Computing & IT > Computer programming
|
Buy Now
Data Science Projects with Python - A case study approach to successful data science projects using Python, pandas, and scikit-learn (Paperback)
Loot Price: R993
Discovery Miles 9 930
|
|
|
Data Science Projects with Python - A case study approach to successful data science projects using Python, pandas, and scikit-learn (Paperback)
Expected to ship within 18 - 22 working days
|
Gain hands-on experience with industry-standard data analysis and
machine learning tools in Python Key Features Tackle data science
problems by identifying the problem to be solved Illustrate
patterns in data using appropriate visualizations Implement
suitable machine learning algorithms to gain insights from data
Book DescriptionData Science Projects with Python is designed to
give you practical guidance on industry-standard data analysis and
machine learning tools, by applying them to realistic data
problems. You will learn how to use pandas and Matplotlib to
critically examine datasets with summary statistics and graphs, and
extract the insights you seek to derive. You will build your
knowledge as you prepare data using the scikit-learn package and
feed it to machine learning algorithms such as regularized logistic
regression and random forest. You'll discover how to tune
algorithms to provide the most accurate predictions on new and
unseen data. As you progress, you'll gain insights into the working
and output of these algorithms, building your understanding of both
the predictive capabilities of the models and why they make these
predictions. By then end of this book, you will have the necessary
skills to confidently use machine learning algorithms to perform
detailed data analysis and extract meaningful insights from
unstructured data. What you will learn Install the required
packages to set up a data science coding environment Load data into
a Jupyter notebook running Python Use Matplotlib to create data
visualizations Fit machine learning models using scikit-learn Use
lasso and ridge regression to regularize your models Compare
performance between models to find the best outcomes Use k-fold
cross-validation to select model hyperparameters Who this book is
forIf you are a data analyst, data scientist, or business analyst
who wants to get started using Python and machine learning
techniques to analyze data and predict outcomes, this book is for
you. Basic knowledge of Python and data analytics will help you get
the most from this book. Familiarity with mathematical concepts
such as algebra and basic statistics will also be useful.
General
Is the information for this product incomplete, wrong or inappropriate?
Let us know about it.
Does this product have an incorrect or missing image?
Send us a new image.
Is this product missing categories?
Add more categories.
Review This Product
No reviews yet - be the first to create one!
|
You might also like..
|
Email address subscribed successfully.
A activation email has been sent to you.
Please click the link in that email to activate your subscription.