Data Science Projects with Python Ebook Tooltip A case study approach to successful data science projects using Python, pandas, and scikit-learn

Afbeeldingen

Inkijkexemplaar

Artikel vergelijken

  • Engels
  • E-book
  • 9781838552602
  • 30 april 2019
  • -35594
Alle productspecificaties
  • Je leest ebooks gemakkelijk op je Kobo e-reader, of op je smartphone of tablet met de bol.com Kobo app. Let op! Ebooks kunnen niet geannuleerd of geretourneerd worden.

Samenvatting

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 Description

Data 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 for

If 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.

Productspecificaties

Inhoud

Taal
en
Bindwijze
E-book
Oorspronkelijke releasedatum
30 april 2019
Ebook Formaat
-35594
Illustraties
Nee

Betrokkenen

Hoofdauteur
Stephen Klosterman
Tweede Auteur
Steve Klosterman
Hoofduitgeverij
Packt Publishing

Lees mogelijkheden

Lees dit ebook op
Desktop (Mac en Windows) | Kobo e-reader | Android (smartphone en tablet) | iOS (smartphone en tablet) | Windows (smartphone en tablet)

Overige kenmerken

Editie
1
Studieboek
Ja

EAN

EAN
9781838552602

Je vindt dit artikel in

Taal
Engels
Beschikbaar in Kobo Plus
Beschikbaar in Kobo Plus
Beschikbaarheid
Leverbaar
Boek, ebook of luisterboek?
Ebook
Nog geen reviews

Prijsinformatie en bestellen

De prijs van dit product is 22 euro en 99 cent.
Direct beschikbaar
Verkoop door bol
Ebook
  • E-book is direct beschikbaar na aankoop
  • E-books lezen is voordelig
  • Dag en nacht klantenservice
  • Veilig betalen
Houd er rekening mee dat je downloadartikelen niet kunt annuleren of retourneren. Bij nog niet verschenen producten kun je tot de verschijningsdatum annuleren.
Zie ook de retourvoorwaarden

Alle bindwijzen en edities (4)

  • 22,99
    Direct beschikbaar
  • 22,99
    Direct beschikbaar
  • 35,99
    2 - 3 weken Tooltip
  • 31,99
    2 - 3 weken Tooltip

Lijst met gekozen artikelen om te vergelijken

Vergelijk artikelen