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Bilddaten Augmentieren mit Keras

Jousef Murad

Daten Augmentieren mit Keras

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What's inside

Syllabus

Datenaugmentierung mit Keras

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Vermittelt Fertigkeiten und Kenntnisse, die für die berufliche Weiterentwicklung unerlässlich sind
Entwickelt Kernkompetenzen in der Datenaufbereitung mit Keras
Bietet eine umfassende Untersuchung der Datenaufbereitungstechniken
Vermittelt die praktische Anwendung von Datenaufbereitung für die Verbesserung von Machine-Learning-Modellen
Bietet Einblicke in die neuesten Entwicklungen in der Datenaufbereitung mit Keras

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Career center

Learners who complete Bilddaten Augmentieren mit Keras will develop knowledge and skills that may be useful to these careers:
Data Scientist
Data Scientists use their knowledge of data analysis, machine learning, and statistics to solve business problems. They work with businesses to identify their data needs and then develop solutions that use data to improve decision-making. Keras is a powerful tool for data analysis and machine learning. It can be used to preprocess data, build machine learning models, and evaluate model performance. This makes it an ideal tool for Data Scientists who want to use data to solve business problems.
Machine Learning Engineer
Machine Learning Engineers design, build, and maintain machine learning systems. These systems can be used for a variety of purposes, such as image recognition, natural language processing, and speech recognition. Machine Learning Engineers use their knowledge of machine learning algorithms and software to develop systems that can learn from data and make predictions. Keras is a popular framework for building machine learning models. It is easy to use and has a wide range of features. This makes it a good choice for Machine Learning Engineers who want to build high-performance machine learning systems.
Data Analyst
Data Analysts use specialized computer software to analyze large amounts of complex data. The data may come from a variety of sources, such as surveys, experiments, or business transactions. Data Analysts use their analytical skills to identify patterns and trends in the data, and then they develop reports and presentations that communicate their findings to decision-makers. Keras is a powerful tool for data analysis. It can be used to preprocess data, build machine learning models, and evaluate model performance. This makes it an ideal tool for Data Analysts who want to use data to solve business problems.
Software Engineer
Software Engineers design, build, and maintain software systems. They work with businesses to identify their software needs and then develop solutions that meet those needs. Software Engineers use their knowledge of programming languages and software development tools to build high-quality software systems. Keras is a popular framework for building machine learning models. It is easy to use and has a wide range of features. This makes it a good choice for Software Engineers who want to build machine learning systems.
Data Engineer
Data Engineers design, build, and maintain data pipelines. These pipelines are used to collect, clean, and store data. Data Engineers use their knowledge of data engineering tools and technologies to build pipelines that can handle large volumes of data. They also work with businesses to ensure that data pipelines are meeting their needs. Keras is a popular framework for building machine learning models. It is easy to use and has a wide range of features. This makes it a good choice for Data Engineers who want to build machine learning systems that can handle large volumes of data.
Business Analyst
Business Analysts work with businesses to identify their business needs and then develop solutions that meet those needs. They use their knowledge of business analysis techniques and tools to analyze business processes and identify areas for improvement. Keras is a powerful tool for data analysis. It can be used to preprocess data, build machine learning models, and evaluate model performance. This makes it an ideal tool for Business Analysts who want to use data to solve business problems.
Product Manager
Product Managers work with businesses to develop and launch new products. They work with engineers, designers, and marketing teams to ensure that products meet the needs of customers. Product Managers use their knowledge of product development and management techniques to launch successful products. Keras is a popular framework for building machine learning models. It is easy to use and has a wide range of features. This makes it a good choice for Product Managers who want to build machine learning systems that can be used to improve products.
Statistician
Statisticians use mathematical and statistical models to analyze data. They use their models to draw conclusions about the population from which the data was collected. Statisticians use their knowledge of statistics and data analysis to help businesses make informed decisions.
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data. They use their models to make predictions about the future performance of financial markets. Quantitative Analysts use their knowledge of mathematics, statistics, and finance to develop models that can help investors make informed investment decisions. Keras is a powerful tool for data analysis. It can be used to preprocess data, build machine learning models, and evaluate model performance. This makes it an ideal tool for Quantitative Analysts who want to use data to make predictions about the future performance of financial markets.
Risk Analyst
Risk Analysts use data to identify and assess risks. They use their assessments to help businesses make informed decisions about how to manage risk. Risk Analysts use their knowledge of risk management techniques and tools to develop models that can help businesses identify and assess risks.
Data Journalist
Data Journalists use data to tell stories. They work with data to identify trends and patterns and then write articles and create visualizations that communicate their findings to the public. Keras is a powerful tool for data analysis. It can be used to preprocess data, build machine learning models, and evaluate model performance. This makes it an ideal tool for Data Journalists who want to use data to tell stories.
Operations Research Analyst
Operations Research Analysts use mathematical and statistical models to solve business problems. They use their models to optimize business processes and improve efficiency. Operations Research Analysts use their knowledge of operations research techniques and tools to develop models that can help businesses make better decisions.
Market Researcher
Market Researchers use data to understand consumer behavior. They use their research to help businesses develop new products and marketing campaigns. Market Researchers use their knowledge of marketing research techniques and tools to conduct surveys, focus groups, and other research activities. Keras is a powerful tool for data analysis. It can be used to preprocess data, build machine learning models, and evaluate model performance. This makes it an ideal tool for Market Researchers who want to use data to understand consumer behavior.
Data Architect
Data Architects design and build data systems. They work with businesses to identify their data needs and then develop systems that can meet those needs. Data Architects use their knowledge of data architecture techniques and tools to build systems that can store and manage large volumes of data.
Database Administrator
Database Administrators maintain and manage database systems. They work with businesses to ensure that database systems are running smoothly and efficiently. Database Administrators use their knowledge of database administration techniques and tools to maintain databases and ensure that data is secure.

Reading list

We've selected seven 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 Bilddaten Augmentieren mit Keras.
Dieses Buch bietet einen umfassenden Überblick über Deep Learning mit Python und behandelt dabei auch Datenaugmentation mit Keras. Es ist besonders nützlich als Begleitlektüre zum Kurs, da es Hintergrundwissen und praktische Beispiele liefert.
Dieses Buch bietet einen umfassenden Überblick über Machine Learning mit TensorFlow 2 und Keras und behandelt dabei auch Datenaugmentation als wichtiges Thema. Es ist besonders nützlich als Begleitlektüre zum Kurs, da es Hintergrundwissen und praktische Beispiele liefert.
Dieses Buch bietet einen Überblick über künstliche Intelligenz mit Python und behandelt dabei auch Datenaugmentation. Es ist eine gute Wahl für Anfänger, die ihr Wissen über KI erweitern möchten.
Dieses Buch konzentriert sich auf Deep Learning für die medizinische Bildanalyse und behandelt dabei auch Datenaugmentation für medizinische Bilddaten. Es ist eine wertvolle Ressource für diejenigen, die sich für medizinische Bildgebung interessieren.
Dieses Buch ist ein Standardwerk in der Deep Learning-Community und deckt auch Generative Adversarial Networks (GANs) ab, die eng mit Datenaugmentation verbunden sind. Es ist eine wertvolle Ressource für diejenigen, die ein tieferes Verständnis von GANs anstreben.
Dieses Buch bietet einen praktischen Überblick über Machine Learning mit Scikit-Learn, Keras und TensorFlow und behandelt dabei auch Datenaugmentation. Es ist eine gute Wahl für Anfänger, die ihr Wissen über Machine Learning erweitern möchten.
Dieses Buch konzentriert sich auf Deep Learning mit Python und TensorFlow und behandelt dabei auch Datenaugmentation. Es ist eine gute Wahl für Anfänger, die ihr Wissen über Deep Learning erweitern möchten.

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