Direkt zum Inhalt
StartseitePython

Kurs

Introduction to Deep Learning in Python

Fortgeschrittener Anfänger
Aktualisierte 02.2025
Learn the fundamentals of neural networks and how to build deep learning models using Keras 2.0 in Python.
Kurs kostenlos starten

Im Lieferumfang enthaltenPremium or Teams

PythonArtificial Intelligence4 Stunden17 Videos50 Übungen3,500 XP252,508Leistungsnachweis

Kostenloses Konto erstellen

oder

Durch Klick auf die Schaltfläche akzeptierst du unsere Nutzungsbedingungen, unsere Datenschutzrichtlinie und die Speicherung deiner Daten in den USA.
Group

Trainierst du 2 oder mehr?

Versuchen DataCamp for Business

Beliebt bei Lernenden in Tausenden Unternehmen

Kursbeschreibung

Discover Deep Learning Applications

Deep learning is the machine learning technique behind the most exciting capabilities in robotics, natural language processing, image recognition, and artificial intelligence. In this 4-hour course, you’ll gain hands-on practical knowledge of how to apply your Python skills to deep learning with the Keras 2.0 library.

Explore Keras Models with a Library Contributor

Taught by ex-Google data scientist and Keras contributor, Dan Becker, this deep learning course explores neural network models and how you can generate predictions with them. The first chapters will grow your understanding of both forward and backward propagation and how they work in practice.

Keras library is a Python library that can help you develop and review deep learning models. Like many Python libraries, it's free, open-source and very user friendly. You’ll start by creating a Keras model and will learn how to compile, fit, and classify it before making predictions. Once you’ve completed this course, you’ll have all the tools you need to build deep neural networks and start experimenting with wider and deeper networks over time.

Delve Further into Deep Learning

This course is part of several machine learning and deep learning tracks, offering you clear pathways to build your skills and experience in this area once you’ve completed the introductory course, whether you want to complete a personal project or move towards a career as a Machine Learning Scientist.

Voraussetzungen

Supervised Learning with scikit-learn
1

Basics of deep learning and neural networks

Kapitel starten
2

Optimizing a neural network with backward propagation

Kapitel starten
3

Building deep learning models with keras

Kapitel starten
4

Fine-tuning keras models

Kapitel starten
Introduction to Deep Learning in Python
Kurs
abgeschlossen

Leistungsnachweis verdienen

Fügen Sie diese Anmeldeinformationen zu Ihrem LinkedIn-Profil, Lebenslauf oder Lebenslauf hinzu
Teilen Sie es in den sozialen Medien und in Ihrer Leistungsbeurteilung

Im Lieferumfang enthaltenPremium or Teams

Jetzt anmelden

Mach mit 15 Millionen Lernende und starte Introduction to Deep Learning in Python heute!

Kostenloses Konto erstellen

oder

Durch Klick auf die Schaltfläche akzeptierst du unsere Nutzungsbedingungen, unsere Datenschutzrichtlinie und die Speicherung deiner Daten in den USA.