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aws cheat sheets

Home » aws cheat sheets » Page 6

AWS Managed Policies For Job Functions

2023-05-02T03:57:38+00:00

AWS managed policies for job functions are policies that contain sets  of permissions required for a specific job function or role (especially in the IT industry). It is designed to simplify the creation of policies by combining the permissions for many services into a single policy. You can attach these policies for job functions to any group, user, or role.  To further understand this, let’s consider the scenario below: Mikee is the new database administrator of a social media startup that leverages on Amazon Web Services. She was assigned to configure the minimum set of permissions in IAM so she [...]

AWS Managed Policies For Job Functions2023-05-02T03:57:38+00:00

Amazon Aurora vs Amazon RDS

2023-04-07T02:17:17+00:00

    Aurora RDS Type of database Relational database Features • MySQL and PostgreSQL compatible. • 5x faster than standard MySQL databases and 3x faster than standard PostgreSQL databases. • Use Parallel Query to run transactional and analytical workloads in the same Aurora database, while maintaining high performance. • You can distribute and load balance your unique workloads across different sets of Aurora DB instances using custom endpoints. • Aurora Serverless allows for on-demand, autoscaling of your Aurora DB instance capacity. • Has several database instance types for different kinds of workloads and support five database engines - MySQL, PostgreSQL, [...]

Amazon Aurora vs Amazon RDS2023-04-07T02:17:17+00:00

Amazon Aurora Machine Learning

2023-05-02T05:15:36+00:00

Amazon Aurora Machine Learning is a proprietary technology of Amazon that enables a native SQL user to integrate Machine Learning-based predictions to an application without knowing or understanding any machine learning algorithms. Machine learning heavily relies on datasets for it to work. You can say that data is the oil that keeps the engine of machine learning running. There is a massive amount of data generated every day. To give you an idea, according to this article, “By 2020, it’s estimated that for every person on earth, 1.7 MB of data will be created every second.”  Almost 2 MB of [...]

Amazon Aurora Machine Learning2023-05-02T05:15:36+00:00

Amazon Comprehend

2023-10-05T02:52:20+00:00

Bookmarks Common Use Cases Concepts Amazon Comprehend Medical Pricing Validate Your Knowledge What is Amazon Comprehend? A managed Natural Language Processing (NLP) service that you can use to extract meaningful information from unstructured texts so you can analyze them in a human-like context. It is an off-the-shelf solution that does not require deep machine learning expertise to get started. Works with social media feeds, web pages, comments, product reviews, articles, or emails. Can analyze texts in real-time by using built-in and custom models. Also offers medical insights and protected health information (PHI) [...]

Amazon Comprehend2023-10-05T02:52:20+00:00

AWS DeepLens

2023-02-28T02:35:11+00:00

AWS DeepLens Cheat Sheet A deep learning-enabled camera for developers A wireless-enabled camera integrated with AWS Cloud Capable of delivering 100GFLOPS of computing power (1 billion operations per second) Contains sample projects at launch to get you started Optimized for Apache MXNet, TensorFlow, and Caffe Integrates with Amazon Rekognition for advanced image analysis Common use cases Developing computer vision applications such as: Face Detection Activity Detection Object Detection Bird Classification  Artistic Style Transfer AWS DeepLens needs 3 AWS services to create a project: Amazon SageMaker  Train/validate custom or pre-trained models  AWS Lambda Preprocessing  Capturing inference Displaying output AWS IoT Greengrass [...]

AWS DeepLens2023-02-28T02:35:11+00:00

Amazon SageMaker

2023-10-14T02:18:09+00:00

Bookmarks Concepts Common Training Data Formats For Built-in Algorithms Input modes for transferring training data Two methods of deploying a model for inference SageMaker features Optimization Amazon SageMaker Monitoring Amazon SageMaker Pricing Validate Your Knowledge Amazon SageMaker Cheat Sheet A fully managed service that allows data scientists and developers to easily build, train, and deploy machine learning models at scale. Provides built-in algorithms that you can immediately use for model training. Also supports custom algorithms through docker containers. One-click model deployment. Concepts Hyperparameters It refers to a set [...]

Amazon SageMaker2023-10-14T02:18:09+00:00

Amazon Lex

2023-06-23T07:39:39+00:00

Amazon Lex Cheat Sheet A service that can help you build conversational interfaces using voice and text. Uses automatic speech recognition (ASR) to convert speech to text. Uses natural language understanding (NLU) for recognizing the intent of the text. Provides highly-engaging user experiences and lifelike conversational interactions. Gets more intelligent over time by using deep learning. Common Use Cases AI Chatbots Informational bots Enterprise Productivity bots Voice Assistants Concepts Bots Performs automated tasks such as ordering food or booking flights. Supports multiple intents - for example, a bot can book a reservation or may choose to cancel it. Intent A [...]

Amazon Lex2023-06-23T07:39:39+00:00

Amazon Elastic Inference

2023-06-23T07:31:25+00:00

Amazon Elastic Inference Cheat Sheet Allows attaching low-cost GPU-powered inference acceleration to EC2 instances, SageMaker instances, or ECS tasks. Reduce machine learning inference costs by up to 75%. Common Use Cases Computer vision Natural language processing Speech recognition Concepts Accelerator A GPU-powered hardware device provisioned.  It is not a part of the hardware where your instance is hosted. Uses AWS PrivateLink endpoint service to attach to the instance over the network. Only a single endpoint service is required in every Availability Zone to connect Elastic Inference accelerator to instances. Features Supports TensorFlow, Apache MXNet, PyTorch, and ONNX models. Can provide [...]

Amazon Elastic Inference2023-06-23T07:31:25+00:00

Amazon Polly

2023-06-23T08:42:51+00:00

Bookmarks Common use cases Concepts Features Pricing Validate Your Knowledge Amazon Polly Cheat Sheet A text-to-speech (TTS) service Uses advanced deep learning technologies to convert text into natural, lifelike speech It supports saving text into MP3, OGG, and PCM file formats. Offers Standard and Neural TTS (NTTS) Common Use Cases Increase customer engagement Language learning applications Helps visually impaired individuals to consume digital content Testing in-game dialogs Voice response Concepts Speech Synthesis Markup Language (SSML) Uses XML-based tags to modify different aspects of the text-to-speech output. Can control pitch, speaking style, speech [...]

Amazon Polly2023-06-23T08:42:51+00:00

Amazon Transcribe

2023-02-28T02:23:15+00:00

Amazon Transcribe Cheat Sheet A fully managed automatic speech recognition (ASR) service. Converts speech into text. It supports a wide variety of audio coding formats such as WAV, MP3, MP4, FLAC, AMR, AMR-WB, Ogg, and WebM. It can process batch and streaming transcriptions. Common Use Cases Transcribing customer calls Meeting transcription Closed captioning Generating metadata to create a searchable archive Concepts A confidence score is between 0 and 100, indicating the probability that a given prediction is correct. Low-fidelity (lo-fi) is a term used to describe audio recordings that exhibit poor sound quality. The term high-fidelity refers to high-quality audio [...]

Amazon Transcribe2023-02-28T02:23:15+00:00

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