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Jousef Murad
Neuronales Netz von Scratch
Register for this course and see more details by visiting:
OpenCourser.com/course/p69sn0/neuronales
What's inside
Syllabus
Module 1
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Beschäftigt sich mit neuronalen Netzwerken, was in der Industrie ein Standard ist
Lehrt neuronale Netzwerke, was den Teilnehmern hilft, KI-Modelle zu erstellen
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Neuronales Netz von Scratch with these
activities:
Organize and review course materials
Show steps
Organizing and reviewing your course materials will help you stay on top of the content and identify areas where you need additional support.
Browse courses on
Note-Taking
Show steps
-
Create a system for organizing your notes, assignments, and other course materials
-
Review your materials regularly to reinforce your understanding
-
Identify sections or concepts that you may need to revisit or seek additional support for
Read 'Deep Learning' by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
Show steps
This comprehensive textbook provides an in-depth overview of the field of deep learning, covering both theoretical foundations and practical applications.
View
Deep Learning. Das umfassende Handbuch
on Amazon
Show steps
-
Read through the chapters systematically, taking notes and highlighting important concepts
-
Work through the exercises and assignments provided in the book
-
Discuss the book's content with peers or a mentor
Review basics of neural networks
Show steps
Refreshing your foundational knowledge of neural networks will help you better understand and absorb the more advanced concepts covered in this course.
Browse courses on
Neural Networks
Show steps
-
Review textbooks or online resources on neural networks
-
Complete practice problems or exercises on basic neural network concepts
-
Discuss neural network fundamentals with a peer or mentor
Three other activities
Expand to see all activities and additional details
Show all six activities
Participate in peer study groups or discussions
Show steps
Engaging with peers through study groups or discussions can provide diverse perspectives, foster understanding, and improve your overall learning experience.
Show steps
-
Join or form a study group with classmates or fellow learners
-
Meet regularly to discuss course materials, share insights, and work on problems together
-
Participate in online discussions or forums related to the course topics
Implement different neural network architectures
Show steps
Implementing various neural network architectures will provide you with hands-on experience and a deeper understanding of their strengths and limitations.
Show steps
-
Choose a programming language and framework for neural network development
-
Implement a simple feedforward neural network
-
Experiment with different activation functions, hidden layers, and optimization algorithms
-
Compare the performance of different architectures on a given dataset
Develop a neural network for a specific task
Show steps
Creating your own neural network for a specific task will allow you to apply the concepts you've learned and gain practical experience.
Browse courses on
Machine Learning Projects
Show steps
-
Identify a problem or task that can be solved using a neural network
-
Gather and prepare the necessary data
-
Design and implement a neural network architecture for the task
-
Train and evaluate the neural network
-
Deploy and use the neural network to solve the problem or task
Organize and review course materials
Show steps
Organizing and reviewing your course materials will help you stay on top of the content and identify areas where you need additional support.
Browse courses on
Note-Taking
Show steps
Show steps
Show steps
- Create a system for organizing your notes, assignments, and other course materials
- Review your materials regularly to reinforce your understanding
- Identify sections or concepts that you may need to revisit or seek additional support for
Read 'Deep Learning' by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
Show steps
This comprehensive textbook provides an in-depth overview of the field of deep learning, covering both theoretical foundations and practical applications.
View
Deep Learning. Das umfassende Handbuch
on Amazon
Show steps
Show steps
Show steps
- Read through the chapters systematically, taking notes and highlighting important concepts
- Work through the exercises and assignments provided in the book
- Discuss the book's content with peers or a mentor
Review basics of neural networks
Show steps
Refreshing your foundational knowledge of neural networks will help you better understand and absorb the more advanced concepts covered in this course.
Browse courses on
Neural Networks
Show steps
Show steps
Show steps
- Review textbooks or online resources on neural networks
- Complete practice problems or exercises on basic neural network concepts
- Discuss neural network fundamentals with a peer or mentor
Three other activities
Expand to see all activities and additional details
Show all six activities
Participate in peer study groups or discussions
Show steps
Engaging with peers through study groups or discussions can provide diverse perspectives, foster understanding, and improve your overall learning experience.
Show steps
Show steps
Show steps
- Join or form a study group with classmates or fellow learners
- Meet regularly to discuss course materials, share insights, and work on problems together
- Participate in online discussions or forums related to the course topics
Implement different neural network architectures
Show steps
Implementing various neural network architectures will provide you with hands-on experience and a deeper understanding of their strengths and limitations.
Show steps
Show steps
Show steps
- Choose a programming language and framework for neural network development
- Implement a simple feedforward neural network
- Experiment with different activation functions, hidden layers, and optimization algorithms
- Compare the performance of different architectures on a given dataset
Develop a neural network for a specific task
Show steps
Creating your own neural network for a specific task will allow you to apply the concepts you've learned and gain practical experience.
Browse courses on
Machine Learning Projects
Show steps
Show steps
Show steps
- Identify a problem or task that can be solved using a neural network
- Gather and prepare the necessary data
- Design and implement a neural network architecture for the task
- Train and evaluate the neural network
- Deploy and use the neural network to solve the problem or task
Career center
Learners who complete Neuronales Netz von Scratch will develop knowledge and skills
that may be useful to these careers:
Deep Learning Engineer
Deep Learning Engineer
A Deep Learning Engineer is responsible for designing, developing, and deploying deep learning models. This course provides a comprehensive overview of deep learning concepts and algorithms, and covers the practical skills needed to build and deploy deep learning models in the real world.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer is responsible for designing, developing, and deploying machine learning models. This course provides a comprehensive overview of machine learning concepts and algorithms, and covers the practical skills needed to build and deploy machine learning models in the real world.
Data Scientist
Data Scientist
A Data Scientist is responsible for collecting, cleaning, analyzing, and interpreting data in order to provide insights that can inform business decisions. This course provides a solid foundation in the principles of data science, including machine learning and deep learning, and covers the latest techniques used by data scientists in industry today.
Artificial Intelligence Engineer
Artificial Intelligence Engineer
An Artificial Intelligence Engineer is responsible for designing, developing, and deploying artificial intelligence systems. This course provides a comprehensive overview of artificial intelligence concepts and algorithms, and covers the practical skills needed to build and deploy artificial intelligence systems in the real world.
Software Engineer
Software Engineer
A Software Engineer is responsible for designing, developing, and maintaining software systems. This course provides a strong foundation in the principles of software engineering, and covers the latest techniques used by software engineers in industry today.
Data Analyst
Data Analyst
A Data Analyst is responsible for collecting, cleaning, and analyzing data in order to provide insights that can inform business decisions. This course provides a solid foundation in the principles of data analysis, and covers the latest techniques used by data analysts in industry today.
Operations Research Analyst
Operations Research Analyst
An Operations Research Analyst is responsible for developing and using mathematical and statistical models to solve complex business problems. This course provides a strong foundation in the principles of operations research, and covers the latest techniques used by operations research analysts in industry today.
Quantitative Analyst
Quantitative Analyst
A Quantitative Analyst is responsible for developing and using mathematical and statistical models to analyze financial data. This course provides a strong foundation in the principles of quantitative analysis, and covers the latest techniques used by quantitative analysts in industry today.
Actuary
Actuary
An Actuary is responsible for assessing and managing financial risks. This course provides a strong foundation in the principles of actuarial science, and covers the latest techniques used by actuaries in industry today.
Financial Analyst
Financial Analyst
A Financial Analyst is responsible for analyzing financial data and making recommendations on investments. This course provides a strong foundation in the principles of financial analysis, and covers the latest techniques used by financial analysts in industry today.
Business Analyst
Business Analyst
A Business Analyst is responsible for analyzing business processes and recommending improvements. This course provides a strong foundation in the principles of business analysis, and covers the latest techniques used by business analysts in industry today.
Management Consultant
Management Consultant
A Management Consultant is responsible for advising businesses on how to improve their operations. This course provides a strong foundation in the principles of management consulting, and covers the latest techniques used by management consultants in industry today.
Product Manager
Product Manager
A Product Manager is responsible for managing the development and launch of new products. This course provides a strong foundation in the principles of product management, and covers the latest techniques used by product managers in industry today.
Project Manager
Project Manager
A Project Manager is responsible for planning, executing, and closing projects. This course provides a strong foundation in the principles of project management, and covers the latest techniques used by project managers in industry today.
Sales Engineer
Sales Engineer
A Sales Engineer is responsible for selling and supporting technical products. This course provides a strong foundation in the principles of sales engineering, and covers the latest techniques used by sales engineers in industry today.
For more career information including salaries, visit:
OpenCourser.com/course/p69sn0/neuronales
Reading list
We've selected 13 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Neuronales Netz von Scratch.
Save
Dieses Buch bietet einen umfassenden Überblick über Deep Learning, einschließlich der Grundlagen, Architekturen und Anwendungen. Es ist ein wertvolles Referenzwerk für alle, die ihr Wissen über Deep Learning vertiefen möchten.
Dieses Buch bietet einen umfassenden Überblick über Mustererkennung und Machine Learning. Es ist ein wertvolles Referenzwerk für alle, die ihr Wissen über Mustererkennung und Machine Learning vertiefen möchten.
Dieses Buch bietet einen umfassenden Überblick über Sprach- und Sprachverarbeitung, einschließlich der Grundlagen, Techniken und Anwendungen. Es ist ein wertvolles Referenzwerk für alle, die ihr Wissen über Sprach- und Sprachverarbeitung vertiefen möchten.
Dieses Buch bietet einen umfassenden Überblick über Informationstheorie, Inferenz und Lernalgorithmen. Es ist ein wertvolles Referenzwerk für alle, die ihr Wissen über Informationstheorie, Inferenz und Lernalgorithmen vertiefen möchten.
Dieses Buch bietet einen umfassenden Überblick über Bayes'sche Argumentation und Machine Learning. Es ist ein wertvolles Referenzwerk für alle, die ihr Wissen über Bayes'sche Argumentation und Machine Learning vertiefen möchten.
Dieses Buch bietet einen umfassenden Überblick über statistische Methoden für Machine Learning. Es ist ein wertvolles Referenzwerk für alle, die ihr Wissen über statistische Methoden im Machine Learning vertiefen möchten.
Dieses Buch bietet einen umfassenden Überblick über probabilistische grafische Modelle. Es ist ein wertvolles Referenzwerk für alle, die ihr Wissen über probabilistische grafische Modelle vertiefen möchten.
Save
Dieses Buch bietet einen umfassenden Überblick über Computervision, einschließlich der Grundlagen, Techniken und Anwendungen. Es ist ein wertvolles Referenzwerk für alle, die ihr Wissen über Computervision vertiefen möchten.
Dieses Buch bietet einen umfassenden Überblick über Deep Reinforcement Learning, einschließlich der Grundlagen, Architekturen und Anwendungen. Es ist ein wertvolles Referenzwerk für alle, die ihr Wissen über Deep Reinforcement Learning vertiefen möchten.
Dieses Buch bietet eine praktische Einführung in die Verarbeitung natürlicher Sprache mit Python. Es ist eine wertvolle Ressource für alle, die ihre praktischen Fähigkeiten in der Verarbeitung natürlicher Sprache verbessern möchten.
Dieses Buch bietet eine praktische Einführung in Machine Learning mit Python-Bibliotheken wie Scikit-Learn, Keras und TensorFlow. Es ist eine wertvolle Ressource für alle, die ihre praktischen Fähigkeiten im Machine Learning verbessern möchten.
Dieses Buch bietet eine praktische Einführung in Deep Learning mit Python. Es ist eine wertvolle Ressource für alle, die ihre praktischen Fähigkeiten im Deep Learning verbessern möchten.
Dieses Buch bietet eine praktische Einführung in Machine Learning mit R. Es ist eine wertvolle Ressource für alle, die ihre praktischen Fähigkeiten im Machine Learning verbessern möchten.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/p69sn0/neuronales
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Effort
1 Stunde
Level
Introductory
Via
Coursera
Institution
Coursera Project Network
Instructor
Jousef Murad
Language
Deutsch
Good to know
Beschäftigt sich mit neuronalen Netzwerken, was in der Industrie ein Standard ist
Lehrt neuronale Netzwerke, was den Teilnehmern hilft, KI-Modelle zu erstellen
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