Data Science

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By Ai Publishing
In stock
$3000 $2100
How Is This Book Different? Most Python books assume you know how to code using Pandas, NumPy, and Matplotlib. But this book does not. The author spends a lot of time teaching you how actually write the simplest codes in Python to achieve machine learning models. In-depth coverage of the Scikit-learn library starts from the third chapter itself. Jumping straight to Scikit-learn makes it easy for you to follow along. The other advantage is  Jupyter Notebook  is used to write and explain the code right through this book. You can access the datasets used in this book easily by downloading them at runtime. You can also access them through the  Datasets  folder in the SharePoint and GitHub repositories. You also get to work on three hands-on mini-projects:
AuthorAi Publishing BindingPaperback
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By Davy Cielen
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Davy Cielen  is one of the founders and managing partners of Optimately where he focuses on leading and developing data science projects and solutions in various sectors and closely follows new developments in data science. Before Optimately he worked on data science and big data projects at a major retailer. Arno Meysman  is one of the founders and managing partners of Optimately where he focuses on leading and developing data science projects and solutions in various sectors and closely follows new developments in data science. Before Optimately he worked on data science and big data projects at a major retailer. Apart from data science he is also into data visualisation and generally "Creating data-driven things that are smart, interactive and pretty". Mohamed Ali  is one of the founders and managing partners of Optimately and Maiton, where they focus on developing data science projects and solutions in various sectors.
AuthorDavy Cielen BindingPaperback
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By Brian Godsey
$4499 $4049
Brian Godsey  holds a PhD in applied mathematics, is active in the academic community, and has been developing statistical software for over 10 years. In the last few years, he has been involved in startups as a co-founder, adviser, and team member.
AuthorBrian Godsey BindingPaperback
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By Jesse Daniel
$4999 $3999
Jesse Daniel  has five years of experience writing applications in Python, including three years working with in the PyData stack (Pandas, NumPy, SciPy, Scikit-Learn). Jesse joined the faculty of the University of Denver in 2016 as an adjunct professor of business information and analytics, where he currently teaches a Python for Data Science course.
AuthorJesse Daniel BindingPaperback
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By Nina Zumel, John Mount
$4999 $3999
Nina Zumel  co-founded Win-Vector, a data science consulting firm in San Francisco. She holds a PH.D. in robotics from Carnegie Mellon and was a content developer for EMC's Data Science and Big Data Analytics Training Course. Nina also contributes to the Win-Vector Blog, which covers topics in statistics, probability, computer science, mathematics and optimization. John Mount  co-founded Win-Vector, a data science consulting firm in San Francisco. He has a Ph.D. in computer science from Carnegie Mellon and over 15 years of applied experience in biotech research, online advertising, price optimization and finance. He contributes to the Win-Vector Blog, which covers topics in statistics, probability, computer science, mathematics and optimization.
AuthorNina Zumel, John Mount BindingPaperback
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By Carl S. Gold
$5999 $4799
Carl Gold  is the Chief Data Scientist at Zuora, Inc, a comprehensive subscription management platform and newly public Silicon Valley "unicorn". Zuora is widely recognized in a leader in all things pertaining to subscription and recurring revenue, with 1,000 customers across a range of industries worldwide. Carl joined Zuora in 2015 and created the predictive analytics system for Zuora's subscriber analysis product, Zuora Insights.
AuthorCarl S. Gold BindingPaperback
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By Bogumil Kaminski
$5999 $4800
Bogumil Kaminski  iis one of the lead developers of DataFrames.jl—the core package for data manipulation in the Julia ecosystem. He has over 20 years of experience delivering data science projects.
AuthorBogumil Kaminski BindingPaperback
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By Jake VanderPlas
In stock
$2054 $1849
Jake VanderPlas  is a software engineer at Google Research, working on tools that support data-intensive research. He maintains a technical blog, Pythonic Perambulations, to share tutorials and opinions related to statistics, open software, and scientific computing in Python. He creates and develops Python tools for use in data-intensive science, including packages like Scikit-Learn, SciPy, AstroPy, Altair, JAX, and many others. He participates in the broader data science community, developing and presenting talks and tutorials on scientific computing topics at various conferences in the data science world.
AuthorJake VanderPlas BindingPaperback
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By Joe Minichino
$5995 $4796
This product will be shipped on 28-02-2023
In  Data Analytics in the AWS Cloud: Building a Data Platform for BI and Predictive Analytics on AWS , accomplished software engineer and data architect Joe Minichino delivers an expert blueprint to storing, processing, analyzing data on the Amazon Web Services cloud platform. In the book, you’ll explore every relevant aspect of data analytics—from data engineering to analysis, business intelligence, DevOps, and MLOps—as you discover how to integrate machine learning predictions with analytics engines and visualization tools.
AuthorJoe Minichino BindingPaperback
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By Mohamed Sabri
In stock
$1114 $947
Who this book is for This book is for data professionals, data scientists, students, or those who are new to the field who wish to stay on top of industry jargon and terminologies used in the field of data science.
AuthorMohamed Sabri BindingPaperback
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By Mark Edmondson
In stock
$1585 $1426
Mark Edmondson  is Senior Data Scientist at IIH Nordic A/S. He is also a Google Developer Expert for Google Analytics and Google Cloud, and has consulted for over 15 years helping global brands with their digital marketing strategy. He contributes to the digital marketing community through his blog and open source contributions, focusing on data science and engineering applications with digital marketing data. Mark  has published several data activation proof of concepts over the years that have been popular within the digital marketing industry, including a web app to measure if certain events affected your data in a statistically significant way; using markov chains with Google Analytics data to predict where users will go so as to prefetch web resources and improve page load speed experience; and using streaming web analytics data to BigQuery to create real-time digital analytics dashboards.
AuthorMark Edmondson BindingPaperback
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By John T.Wolohan
$4999 $4499
Mastering Large Datasets with Python  teaches you to write code that can handle datasets of any size. You’ll start with laptop-sized datasets that teach you to parallelize data analysis by breaking large tasks into smaller ones that can run simultaneously. You’ll then scale those same programs to industrial-sized datasets on a cluster of cloud servers.
AuthorJohn T.Wolohan BindingPaperback
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