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Saravanan Dhandapani
Being the front runner when it comes to cloud infrastructure, AWS has cutting edge services when it comes to machine learning. In this course, Modeling with AWS Machine Learning, you’ll learn to convert your data to an optimal model leveraging AWS SageMaker....
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Being the front runner when it comes to cloud infrastructure, AWS has cutting edge services when it comes to machine learning. In this course, Modeling with AWS Machine Learning, you’ll learn to convert your data to an optimal model leveraging AWS SageMaker....
Read more
Being the front runner when it comes to cloud infrastructure, AWS has cutting edge services when it comes to machine learning. In this course, Modeling with AWS Machine Learning, you’ll learn to convert your data to an optimal model leveraging AWS SageMaker. First, you’ll explore supervised and unsupervised learning algorithms that are built-in to your AWS account and learn how to apply them to a specific business problem. Next, you’ll discover deep learning neural networks architecture and the built-in algorithms provided by AWS that cater specifically to computer vision and language processing domain. Finally, you’ll learn how to train a model on a SageMaker notebook, evaluate the model against the objective metric, and fine-tune the hyperparameters and arrive at an optimally performing model. When you’re finished with this course, you’ll have the skills and knowledge of all the AWS built-in algorithms and train, evaluate, and tune your models that are needed to master AWS SageMaker and clear AWS Machine Learning Specialty certification exam.
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Offers deep learning neural networks architecture and AWS algorithms for computer vision and language processing
Taught by Saravanan Dhandapani, an expert in AWS
Covers supervised and unsupervised learning algorithms built into AWS
Provides hands-on experience by training a model on a SageMaker notebook
Geared towards individuals preparing for the AWS Machine Learning Specialty certification exam
Requires students to have basic knowledge of AWS and machine learning concepts
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Career center
Learners who complete Modeling with AWS Machine Learning will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, build, test, and deploy machine learning models. They work with data scientists to determine the appropriate algorithms and models for a given problem, and then they develop and implement the models using programming languages and software tools. This course can help you build the skills you need to become a Machine Learning Engineer by providing you with a foundation in machine learning algorithms and techniques, as well as experience with AWS SageMaker, a cloud-based platform for building, training, and deploying machine learning models.
Data Scientist
Data Scientist
Data Scientists use their knowledge of statistics, mathematics, and computer science to extract insights from data. They work with businesses to identify problems that can be solved using data, and then they develop and implement solutions using machine learning and other data analysis techniques. This course can help you build the skills you need to become a Data Scientist by providing you with a foundation in machine learning algorithms and techniques, as well as experience with AWS SageMaker, a cloud-based platform for building, training, and deploying machine learning models.
Software Engineer
Software Engineer
Software Engineers design, develop, test, and maintain software applications. They work with businesses to identify problems that can be solved using software, and then they develop and implement solutions using programming languages and software tools. This course can help you build the skills you need to become a Software Engineer by providing you with a foundation in machine learning algorithms and techniques, as well as experience with AWS SageMaker, a cloud-based platform for building, training, and deploying machine learning models.
Cloud Architect
Cloud Architect
Cloud Architects design and manage cloud computing systems. They work with businesses to identify the best cloud computing solutions for their needs, and then they design and implement those solutions. This course can help you build the skills you need to become a Cloud Architect by providing you with a foundation in machine learning algorithms and techniques, as well as experience with AWS SageMaker, a cloud-based platform for building, training, and deploying machine learning models.
Data Analyst
Data Analyst
Data Analysts use their knowledge of statistics, mathematics, and computer science to extract insights from data. They work with businesses to identify problems that can be solved using data, and then they develop and implement solutions using data analysis techniques. This course can help you build the skills you need to become a Data Analyst by providing you with a foundation in machine learning algorithms and techniques, as well as experience with AWS SageMaker, a cloud-based platform for building, training, and deploying machine learning models.
Business Analyst
Business Analyst
Business Analysts work with businesses to identify problems and develop solutions. They use their knowledge of business processes and technology to develop solutions that meet the needs of the business. This course can help you build the skills you need to become a Business Analyst by providing you with a foundation in machine learning algorithms and techniques, as well as experience with AWS SageMaker, a cloud-based platform for building, training, and deploying machine learning models.
Product Manager
Product Manager
Product Managers are responsible for the development and management of products. They work with teams of engineers, designers, and marketers to bring products to market. This course can help you build the skills you need to become a Product Manager by providing you with a foundation in machine learning algorithms and techniques, as well as experience with AWS SageMaker, a cloud-based platform for building, training, and deploying machine learning models.
Project Manager
Project Manager
Project Managers are responsible for planning, organizing, and managing projects. They work with teams of people to complete projects on time and within budget. This course can help you build the skills you need to become a Project Manager by providing you with a foundation in machine learning algorithms and techniques, as well as experience with AWS SageMaker, a cloud-based platform for building, training, and deploying machine learning models.
Consultant
Consultant
Consultants provide advice and guidance to businesses on a variety of topics. They use their knowledge of business processes and technology to help businesses improve their operations. This course can help you build the skills you need to become a Consultant by providing you with a foundation in machine learning algorithms and techniques, as well as experience with AWS SageMaker, a cloud-based platform for building, training, and deploying machine learning models.
Teacher
Teacher
Teachers educate students at all levels, from elementary school to university. They develop and implement lesson plans, assess student learning, and provide guidance and support to students. This course can help you build the skills you need to become a Teacher by providing you with a foundation in machine learning algorithms and techniques, as well as experience with AWS SageMaker, a cloud-based platform for building, training, and deploying machine learning models.
Researcher
Researcher
Researchers conduct research in a variety of fields, including science, engineering, and social sciences. They use their knowledge to develop new technologies, products, and services. This course can help you build the skills you need to become a Researcher by providing you with a foundation in machine learning algorithms and techniques, as well as experience with AWS SageMaker, a cloud-based platform for building, training, and deploying machine learning models.
Writer
Writer
Writers create content for a variety of purposes, including marketing, journalism, and fiction. They use their creativity and writing skills to communicate ideas and stories to readers. This course can help you build the skills you need to become a Writer by providing you with a foundation in machine learning algorithms and techniques, as well as experience with AWS SageMaker, a cloud-based platform for building, training, and deploying machine learning models.
Artist
Artist
Artists create visual art, such as paintings, sculptures, and photographs. They use their creativity and artistic skills to express themselves and communicate their ideas to others. This course can help you build the skills you need to become an Artist by providing you with a foundation in machine learning algorithms and techniques, as well as experience with AWS SageMaker, a cloud-based platform for building, training, and deploying machine learning models.
Musician
Musician
Musicians create music using instruments, their voices, or electronic devices. They use their creativity and musical skills to express themselves and communicate their ideas to others. This course can help you build the skills you need to become a Musician by providing you with a foundation in machine learning algorithms and techniques, as well as experience with AWS SageMaker, a cloud-based platform for building, training, and deploying machine learning models.
Actor
Actor
Actors perform in plays, movies, and television shows. They use their creativity and acting skills to bring characters to life and communicate their ideas to audiences. This course can help you build the skills you need to become an Actor by providing you with a foundation in machine learning algorithms and techniques, as well as experience with AWS SageMaker, a cloud-based platform for building, training, and deploying machine learning models.
For more career information including salaries, visit:
OpenCourser.com/course/s8rlb7/modeling
Reading list
We haven't picked any books for this reading list yet.
Provides a comprehensive overview of machine learning using R. It covers a variety of topics, including supervised learning, unsupervised learning, and deep learning. It valuable resource for developers and data scientists who want to learn more about machine learning using R.
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Provides a beginner's guide to AWS SageMaker. It valuable resource for anyone looking to get started with machine learning on AWS.
Provides a comprehensive overview of machine learning using Python. It covers a variety of topics, including supervised learning, unsupervised learning, and deep learning. It valuable resource for developers and data scientists who want to learn more about machine learning using Python.
Provides a practical guide to using machine learning in a business setting. It covers a variety of topics, including data preparation, model selection, and model deployment. It valuable resource for business professionals who want to learn more about how machine learning can be used to improve their business.
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Provides a comprehensive overview of deep learning using Python. It covers a variety of topics, including convolutional neural networks, recurrent neural networks, and generative adversarial networks. It valuable resource for developers and data scientists who want to learn more about deep learning using Python.
Provides a gentle introduction to machine learning. It great resource for beginners who want to learn more about the basics of machine learning. It covers a variety of topics, including supervised learning, unsupervised learning, and deep learning.
Provides a comprehensive overview of AWS Machine Learning services, including SageMaker. It valuable resource for developers and data scientists who want to get started with machine learning on AWS.
Provides a comprehensive overview of machine learning with big data. It covers a variety of topics, including data preprocessing, feature engineering, and model training. It valuable resource for developers and data scientists who want to learn more about machine learning with big data.
Provides a comprehensive overview of machine learning using Python. It covers a variety of topics, including supervised learning, unsupervised learning, and deep learning. It valuable resource for developers and data scientists who want to learn more about machine learning using Python.
Provides a comprehensive overview of machine learning for cyber security. It covers a variety of topics, including anomaly detection, intrusion detection, and malware analysis. It valuable resource for developers and data scientists who want to learn more about machine learning for cyber security.
Provides a comprehensive overview of machine learning for healthcare. It covers a variety of topics, including disease diagnosis, patient prognosis, and drug discovery. It valuable resource for developers and data scientists who want to learn more about machine learning for healthcare.
Provides a comprehensive overview of machine learning for finance. It covers a variety of topics, including stock market prediction, risk management, and fraud detection. It valuable resource for developers and data scientists who want to learn more about machine learning for finance.
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Provides a comprehensive overview of machine learning for marketing. It covers a variety of topics, including customer segmentation, customer lifetime value prediction, and marketing campaign optimization. It valuable resource for developers and data scientists who want to learn more about machine learning for marketing.
Provides a comprehensive overview of interpretable machine learning. It covers a variety of topics, including model interpretability, model explainability, and model debugging. It valuable resource for developers and data scientists who want to learn more about interpretable machine learning.
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Provides a probabilistic perspective on supervised learning, covering topics such as Bayesian inference and graphical models.
Provides a comprehensive overview of supervised learning, covering both theoretical and practical aspects.
Provides a theoretical foundation for supervised learning, covering topics such as linear regression, logistic regression, and support vector machines.
Provides a practical introduction to supervised learning, using popular Python libraries such as scikit-learn, Keras, and TensorFlow.
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Provides a comprehensive overview of supervised learning, deep learning, and related topics, such as neural networks and reinforcement learning.
Provides a broad overview of supervised learning, covering the fundamental concepts, algorithms, and applications.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/s8rlb7/modeling
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Time
2 hours
Via
Pluralsight
Instructor
Saravanan Dhandapani
This course belongs to a
collection
called
AWS Certified Machine Learning – Specialty (MLS-C01). It's comprised of six courses:
- Fundamentals of Machine Learning on AWS
- Exploratory Data Analysis with AWS Machine Learning
- Modeling with AWS Machine Learning (viewing)
- Implementing and Operating AWS Machine Learning Solutions
- Data Engineering with AWS Machine Learning
- Demystifying the AWS Certified Machine Learning Specialty Exam
Good to know
Offers deep learning neural networks architecture and AWS algorithms for computer vision and language processing
Taught by Saravanan Dhandapani, an expert in AWS
Covers supervised and unsupervised learning algorithms built into AWS
Provides hands-on experience by training a model on a SageMaker notebook
Geared towards individuals preparing for the AWS Machine Learning Specialty certification exam
Requires students to have basic knowledge of AWS and machine learning concepts
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