The Data Science Workshop : A New, Interactive Approach to Learning Data Science

The Data Science Workshop : A New, Interactive Approach to Learning Data Science

Enregistré dans:

Détails bibliographiques
Auteur principal:	So, Anthony. (Auteur)
Autres auteurs:	Joseph, Thomas V.. (Auteur), Worsley, Andrew., Asare, Samuel.
Support:	E-Book
Langue:	Anglais
Publié:	Birmingham : Packt Publishing, 2020.
Autres localisations:	Voir dans le Sudoc
Accès en ligne:	Accès à l'E-book

Documents similaires

The Data Science Workshop : Learn how you can build machine learning models and create your own real-world data science projects
par: So, Anthony.
Publié: (2020)

The Applied Data Science Workshop : Get started with the applications of data science and techniques to explore and assess data effectively
par: Galea, Alex.
Publié: (2020)

The Applied Artificial Intelligence Workshop : Start working with AI today, to build games, design decision trees, and train your own machine learning models
par: So, Anthony.
Publié: (2020)

The Clojure Workshop : A New, Interactive Approach to Learning Clojure
par: Fahey, Joseph (19..-....; auteur d'un livre en informatique).
Publié: (2020)

The SQL Workshop : A New, Interactive Approach to Learning SQL
par: Solomon, Frank.
Publié: (2019)

The Data Visualization Workshop : A self-paced, practical approach to transforming your complex data into compelling, captivating graphics
par: Dobler, Mario.
Publié: (2020)

The C++ Workshop : A New Interactive Approach tu Learning C++
par: Green, Dale.
Publié: (2020)

The Supervised Learning Workshop : A New, Interactive Approach to Understanding Supervised Learning Algorithms
par: Bateman, Blaine.
Publié: (2020)

The JavaScript Workshop : A New, Interactive Approach to Learning JavaScript
par: Labrecque, Joseph.
Publié: (2019)

The HTML and CSS Workshop : A New, Interactive Approach to Learning HTML and CSS
par: Coulson, Lewis.
Publié: (2019)

The Data Wrangling Workshop : Create your own actionable insights using data from multiple raw sources
par: Lipp, Brian.
Publié: (2020)

The Data Analysis Workshop : Solve business problems with state-of-the-art data analysis models, developing expert data analysis skills along the way
par: Govindan, Gururajan.
Publié: (2020)

The Statistics and Machine Learning with R Workshop : Unlock the power of efficient data science modeling with this hands-on guide
par: Peng, Liu.

The Tableau Workshop : A practical guide to the art of data visualization with Tableau
par: Gupta, Sumit.
Publié: (2022)

Streamlit for Data Science : Create interactive data apps in Python
par: Richards, Tyler.

Data science fundamentals and practical approaches : understand why data science is the next
par: Nandi, Gypsy.

Data Science Projects with Python : A case study approach to successful data science projects using Python, pandas, and scikit-learn
par: Klosterman, Stephen.
Publié: (2019)

The Unsupervised Learning Workshop : Get started with unsupervised learning algorithms and simplify your unorganized data to help make future predictions
par: Jones, Aaron.
Publié: (2020)

The Pandas Workshop : A comprehensive guide to using Python for data analysis with real-world case studies
par: Bateman, Blaine.
Publié: (2022)

Data Science for IoT Engineers : A Systems Analytics Approach
par: Madhavan, P. G..

The MySQL Workshop : A practical guide to working with data and managing databases with MySQL
par: Pettit, Thomas.
Publié: (2022)

The @Ansible Workshop : Hands-On Learning For Rapid Mastery
par: El Amri, Aymen.

Ethical Hacking Workshop : Explore a practical approach to learning and applying ethical hacking techniques for effective cybersecurity
par: Pillay, Rishalin.

Preparing, designing, leading workshops : A humanistic approach
par: Cooper, S.
Publié: (1980)

Learn Data Science from Scratch : Mastering ML and NLP with Python in a step-by-step approach
par: Padman, Pratheerth.

R for data science
par: Dan, Toomey (19XX-...).
Publié: (2014)

Principles of data science
par: Ozdemir, Sinan.
Publié: (2016)

Data Science for Dummies
par: Pierson, Lillian.

Responsible Data Science
par: Fleming, Grant.

Python for data science
par: Mueller, John Paul (1958-....).
Publié: (2019)

Java for data science
par: Reese, Richard M..
Publié: (2017)

Scala for data science
par: Bugnion, Pascal.
Publié: (2016)

Spark for Data Science
par: Duvvuri, Srinivas.
Publié: (2016)

Clojure for data science
par: Garner, Henry.
Publié: (2015)

Data Science with Machine Learning : Python Interview Questions
par: Narayanan, Vishwanathan.

Data Science with Python : Combine Python with machine learning principles to discover hidden patterns in raw data
par: Chopra, Rohan.
Publié: (2019)

Principles of Data Science : A beginner's guide to essential math and coding skills for data fluency and machine learning
par: Ozdemir, Sinan.

Data Science for Web3 : A comprehensive guide to decoding blockchain data with data analysis basics and machine learning cases
par: Areco, Gabriela Castillo.

Statistics for Data Science : Leverage the power of statistics for Data Analysis, Classification, Regression, Machine Learning, and Neural Networks
par: Miller, James D..
Publié: (2017)

Data science with Jupyter : master data science skills with easy-to-follow Python examples
par: Gupta, Prateek.

Université catholique de l'Ouest - Bibliothèques - 3 place André Leroy - BP10808 - 49008 ANGERS Cedex 1