AWS SageMaker, Machine Learning and AI with Python
This is the code repository for AWS SageMaker, Machine learning, and AI with Python. It contains all the supporting project files necessary to work through the video course from start to finish.
About the Video Course
This course is designed to make you an expert in AWS machine learning, and it teaches you how to convert your cool ideas into highly scalable products in a matter of days. The biggest challenge for a data science professional is how to convert proof-of-concept models into actual products that your customers can use. There are several courses on machine learning that teach you how to build models in R, Python, Matlab, and so forth. However, converting a model into a scalable solution and integrating it with your existing application requires a lot of effort and development. The real success of your ideas and concepts depends on how soon you can put them into the hands of your customers. With the AWS Machine Learning service, you can easily conduct experiments and test your concepts. Once you are happy, you can instantly scale them to support millions of requests. No separate development work is needed.
- Develop intelligent applications using AI to add ML models in your app using the AWS AI toolkit
- Execute Amazon SageMaker to build, train, tune and deploy your model
- Train your text data and identify relationships between different forms of text using Amazon Comprehend
- Analyze deep learning models visually using the physical camera of Amazon DeepLens
- Build and integrate your own Amazon Alexa Chatbot to third-party chat applications
- Turn text into lifelike speech using Amazon Polly and stream it on your application for real-time playback
- Implement Amazon Rekognition for face detection, video and image indexing and sentimental analysis