We may earn an affiliate commission when you visit our partners.
Deep Learning Topics with Computer Vision and NLP
Soham Chatterjee
Soham Chatterjee
Master Deep Learning with Computer Vision in our online training course. Learn to train, fine-tune, and deploy deep learning models using Amazon SageMaker.
Prerequisite details
Read more
Master Deep Learning with Computer Vision in our online training course. Learn to train, fine-tune, and deploy deep learning models using Amazon SageMaker.
Prerequisite details
Read more
Master Deep Learning with Computer Vision in our online training course. Learn to train, fine-tune, and deploy deep learning models using Amazon SageMaker.
Prerequisite details
To optimize your success in this program, we've created a list of prerequisites and recommendations to help you prepare for the curriculum. Prior to enrolling, you should have the following knowledge:
- PyTorch
- Deep learning
You will also need to be able to communicate fluently and professionally in written and spoken English.
Register for this course and see more details by visiting:
OpenCourser.com/course/wm939a/deep
What's inside
Syllabus
In this lesson, we will give a background around Deep Learning for Computer Vision and NLP and preparing you to be successful in the rest of this course.
Read more
Syllabus
In this lesson, we will give a background around Deep Learning for Computer Vision and NLP and preparing you to be successful in the rest of this course.
Read more
In this lesson, you will learn about neural networks, cost functions, optimization, and how to train a neural network.
In this lesson you will learn about Model Architectures, Convolutions, and Fine-tuning.
In this lesson, you will learn how to apply all you have learned about deep learning in AWS SageMaker.
In this project, you will use AWS SageMaker to finetune a pretrained model and perform a image classification using profiling, debugging, and hyperparameter tuning.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Explores deep learning for computer vision and NLP, setting learners on a path to success in the field
Taught by Soham Chatterjee, an experienced instructor in deep learning
Provides hands-on experience with AWS SageMaker, a popular cloud platform for machine learning
Covers fundamental concepts of deep learning, such as neural networks, cost functions, and optimization
Guides learners through building, fine-tuning, and deploying deep learning models, providing a comprehensive understanding of the process
Assumes prior knowledge of PyTorch and deep learning, making it suitable for learners with a solid foundation in these areas
Save this course
Save Deep Learning Topics with Computer Vision and NLP to your list so you can find it easily later:
Save
Save
Activities
Coming soon
We're preparing activities for
Deep Learning Topics with Computer Vision and NLP.
These are activities you can do either before, during, or after a course.
Career center
Learners who complete Deep Learning Topics with Computer Vision and NLP will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data Scientists typically require a master's degree in computer science or a similar discipline. They also generally require 1-2 years of experience. Those who wish to stand out in this field will have knowledge of Deep Learning, PyTorch, and computer vision. This course teaches you how to train, fine-tune, and deploy deep learning models using Amazon SageMaker. These skills are essential for those who wish to succeed in this field.
Computer Vision Engineer
Computer Vision Engineer
Computer Vision Engineers typically require a master's degree in computer science or a similar discipline. They also generally require 1-2 years of experience. Those who wish to stand out in this field will have knowledge of Deep Learning, PyTorch, and computer vision. This course teaches you how to train, fine-tune, and deploy deep learning models using Amazon SageMaker. These skills are essential for those who wish to succeed in this field.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers generally require a master's degree in computer science or a similar discipline, and many entry-level jobs require 1-2 years of experience. Those with knowledge of Deep Learning, PyTorch, and computer vision may find additional success in this field. This course teaches you how to train, fine-tune, and deploy deep learning models using Amazon SageMaker. These skills are essential for those who wish to succeed in this field.
Artificial Intelligence Engineer
Artificial Intelligence Engineer
Artificial Intelligence Engineers typically require a bachelor's degree in a computer science, engineering, or mathematics related field. They may also require 1-2 years of experience. Those with knowledge of Deep Learning, PyTorch, and computer vision may find additional success in this field. This course teaches you how to train, fine-tune, and deploy deep learning models using Amazon SageMaker. These skills are essential for those who wish to succeed in this field.
Natural Language Processing Engineer
Natural Language Processing Engineer
Natural Language Processing Engineers typically require a master's degree in computer science or a similar discipline. They also generally require 1-2 years of experience. Those who wish to stand out in this field will have knowledge of Deep Learning, PyTorch, and computer vision. This course teaches you how to train, fine-tune, and deploy deep learning models using Amazon SageMaker. These skills are essential for those who wish to succeed in this field.
Deep Learning Engineer
Deep Learning Engineer
Deep Learning Engineers typically require a master's degree in computer science or a similar discipline. They also generally require 1-2 years of experience. Those who wish to stand out in this field will have knowledge of Deep Learning, PyTorch, and computer vision. This course teaches you how to train, fine-tune, and deploy deep learning models using Amazon SageMaker. These skills are essential for those who wish to succeed in this field.
Research Scientist
Research Scientist
Research Scientists typically require a PhD in computer science or a similar discipline. They may also require 1-2 years of experience. Those with knowledge of Deep Learning, PyTorch, and computer vision may find additional success in this field. This course teaches you how to train, fine-tune, and deploy deep learning models using Amazon SageMaker. These skills are essential for those who wish to succeed in this field.
Data Analyst
Data Analyst
Data Analysts typically require a bachelor's degree in a computer science, engineering, or mathematics related field. They may also require 1-2 years of experience. Those with knowledge of Deep Learning, PyTorch, and computer vision may find additional success in this field. This course teaches you how to train, fine-tune, and deploy deep learning models using Amazon SageMaker. These skills are essential for those who wish to succeed in this field.
Technical Writer
Technical Writer
Technical Writers typically require a bachelor's degree in a computer science or similar related field. Those with knowledge of Deep Learning, PyTorch, and computer vision may find additional success in this field. This course teaches you how to train, fine-tune, and deploy deep learning models using Amazon SageMaker. These skills are essential for those who wish to succeed in this field.
Consultant
Consultant
Consultants typically require a bachelor's degree in a business or computer science related field. They may also require 1-2 years of experience. Those with knowledge of Deep Learning, PyTorch, and computer vision may find additional success in this field. This course teaches you how to train, fine-tune, and deploy deep learning models using Amazon SageMaker. These skills are essential for those who wish to succeed in this field.
Business Analyst
Business Analyst
Business Analysts typically require a bachelor's degree in a business or computer science related field. They may also require 1-2 years of experience. Those with knowledge of Deep Learning, PyTorch, and computer vision may find additional success in this field. This course teaches you how to train, fine-tune, and deploy deep learning models using Amazon SageMaker. These skills are essential for those who wish to succeed in this field.
Software Engineer
Software Engineer
Software Engineers typically require a bachelor's degree in a computer science, engineering, or mathematics related field. They may also require 1-2 years of experience. Those with knowledge of Deep Learning, PyTorch, and computer vision may find additional success in this field. This course teaches you how to train, fine-tune, and deploy deep learning models using Amazon SageMaker. These skills are essential for those who wish to succeed in this field.
Product Manager
Product Manager
Product Managers typically require a bachelor's degree in a business or computer science related field. They may also require 1-2 years of experience. Those with knowledge of Deep Learning, PyTorch, and computer vision may find additional success in this field. This course teaches you how to train, fine-tune, and deploy deep learning models using Amazon SageMaker. These skills are essential for those who wish to succeed in this field.
Project Manager
Project Manager
Project Managers typically require a bachelor's degree in a business or computer science related field. They may also require 1-2 years of experience. Those with knowledge of Deep Learning, PyTorch, and computer vision may find additional success in this field. This course teaches you how to train, fine-tune, and deploy deep learning models using Amazon SageMaker. These skills are essential for those who wish to succeed in this field.
Sales Engineer
Sales Engineer
Sales Engineers typically require a bachelor's degree in a computer science or engineering related field. They may also require 1-2 years of experience. Those with knowledge of Deep Learning, PyTorch, and computer vision may find additional success in this field. This course teaches you how to train, fine-tune, and deploy deep learning models using Amazon SageMaker. These skills are essential for those who wish to succeed in this field.
For more career information including salaries, visit:
OpenCourser.com/course/wm939a/deep
Reading list
We've selected ten 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
Deep Learning Topics with Computer Vision and NLP.
Provides a comprehensive introduction to deep learning for computer vision, covering topics such as image classification, object detection, and image segmentation. It is written in a clear and concise style, and it includes numerous code examples and exercises.
Provides a comprehensive introduction to natural language processing with PyTorch, covering topics such as text classification, named entity recognition, and machine translation. It is written in a clear and concise style, and it includes numerous code examples and exercises.
Provides a comprehensive introduction to deep learning for coders, covering topics such as image classification, object detection, and image segmentation. It is written in a clear and concise style, and it includes numerous code examples and exercises.
Provides a comprehensive introduction to deep learning for natural language processing, covering topics such as text classification, named entity recognition, and machine translation. It is written in a clear and concise style, and it includes numerous code examples and exercises.
Save
Provides a comprehensive introduction to computer vision, covering topics such as image formation, image processing, and object recognition. It is written in a clear and concise style, and it includes numerous code examples and exercises.
Provides a comprehensive introduction to natural language processing, covering topics such as text classification, named entity recognition, and machine translation. It is written in a clear and concise style, and it includes numerous code examples and exercises.
Save
Provides a comprehensive introduction to data mining, covering topics such as data preprocessing, data clustering, and data classification. It is written in a clear and concise style, and it includes numerous code examples and exercises.
Provides a comprehensive introduction to machine learning from a probabilistic perspective, covering topics such as supervised learning, unsupervised learning, and reinforcement learning. It is written in a clear and concise style, and it includes numerous code examples and exercises.
Provides a comprehensive introduction to pattern recognition and machine learning, covering topics such as supervised learning, unsupervised learning, and reinforcement learning. It is written in a clear and concise style, and it includes numerous code examples and exercises.
Provides a comprehensive introduction to statistical learning, covering topics such as supervised learning, unsupervised learning, and reinforcement learning. It is written in a clear and concise style, and it includes numerous code examples and exercises.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/wm939a/deep
Share
Similar courses
Here are nine courses similar to
Deep Learning Topics with Computer Vision and NLP.
AWS Computer Vision: Getting Started with GluonCV
OpenCourser.com/course/pufjft/aws
AWS Computer Vision: Getting Started with GluonCV
Most relevant
Generative AI Foundations for Cloud
OpenCourser.com/course/0854aw/generative
Generative AI Foundations for Cloud
Most relevant
Image Classification on Autopilot with AWS AutoGluon
OpenCourser.com/course/s32sal/image
Image Classification on Autopilot with AWS AutoGluon
Most relevant
Build, Train, and Deploy Machine Learning Models with Amazon SageMaker 1
OpenCourser.com/course/080xb8/build
Build, Train, and Deploy Machine Learning Models with...
Most relevant
TensorFlow for CNNs: Transfer Learning
OpenCourser.com/course/p7kb3k/tensorflow
TensorFlow for CNNs: Transfer Learning
Most relevant
TensorFlow for CNNs: Learn and Practice CNNs
OpenCourser.com/course/6dk3fz/tensorflow
TensorFlow for CNNs: Learn and Practice CNNs
Most relevant
Building Recommender Systems with Machine Learning and AI
OpenCourser.com/course/4rvp8t/building
Building Recommender Systems with Machine Learning and AI
Most relevant
TensorFlow for CNNs: Multi-Class Classification
OpenCourser.com/course/win4h6/tensorflow
TensorFlow for CNNs: Multi-Class Classification
Most relevant
Deep Learning Fundamentals with Keras
OpenCourser.com/course/2lartu/deep
Deep Learning Fundamentals with Keras
Most relevant
Effort
4 weeks
Via
Udacity
Instructor
Soham Chatterjee
Language
English
Good to know
Explores deep learning for computer vision and NLP, setting learners on a path to success in the field
Taught by Soham Chatterjee, an experienced instructor in deep learning
Provides hands-on experience with AWS SageMaker, a popular cloud platform for machine learning
Covers fundamental concepts of deep learning, such as neural networks, cost functions, and optimization
Guides learners through building, fine-tuning, and deploying deep learning models, providing a comprehensive understanding of the process
Assumes prior knowledge of PyTorch and deep learning, making it suitable for learners with a solid foundation in these areas
Our mission
OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.
Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.
Find this site helpful? Tell a friend about us.
Affiliate disclosure
We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.
Your purchases help us maintain our catalog and keep our servers humming without ads.
Thank you for supporting OpenCourser.
© 2016 - 2024 OpenCourser