1. Amazon Rekognition
   1. API, Deep learning tech
   2. Analysis Types
      1. Images
         1. jpeg, png
            1. 15MB in S3, 5MB image byte array
      2. Video
         1. H. 264 files in MPEG-4 (. mp4) or MOV format
            1. 10Gb files up to 6 horas
   3. Benefits
      1. Simple Integration
         1. APIS
            1. easy to use / No ML expertise
         2. Fully Managed
            1. Responde/app latency
         3. Continually Learning
      2. Batch & real-time
         1. Streaming video - Kinesis Video
         2. Images - S3
         3. Large Jobs
            1. thounsands imgees/video S3/Kinese - Batch
      3. Low Cost
      4. Security
         1. User verification
   4. Features
      1. Object, scene, activiy, detection
         1. specific activities happening inthe scene
      2. Facial Recognition
         1. Private repository,
            1. Crowd-mode face detection
            2. up to 100 faces in a single images
      3. Unsafe content detextion
         1. Inappropriate content
            1. Explict/Moderation Levels Suggestive
      4. Facial Analysis
         1. Demografic data / Emotion
            1. Gender, gesture, general attributes, age
         2. Construct timeline of the emotions
      5. Celebrity Recognition
         1. Well-know people
            1. Subtopic 1
         2. Categorization
            1. Marketing/news advertising media
      6. Text in images
         1. real world images, caption, producto naemes, name street,license plates
   5. Pricing
      1. # Images or mins videos analyzed
      2. Free tier
         1. Image analysis: During the free tier period you can analyze 5,000 images per month for free each, in Group 1 and Group 2 APIs.
         2. Face metadata storage: During the free tier period, you can store 1,000 face metadata objects per month for free.
2. Amazon Textract
   1. Extract any text and data from any document using machine learning and without manual effort
   2. ML Models, Millions of docs
      1. Uploaded docs
   3. OCR, Docs Analysis Detect/Extract
      1. Printed Text
      2. Handwriting
      3. Structured data
      4. Tables
   4. Returns
      1. Confidence Score
      2. Extracted data
         1. Bounding Box Coordinates
         2. Doc Location
   5. Benefits
      1. Beyond OCR
         1. Detects Data
         2. OCR
            1. Legal docs/ Scan a book
            2. Extract: texts, Relationships, strucuture
      2. Doc Processing
         1. Loan Processing
         2. Invoices
         3. Receipts
      3. App Integrations
         1. Simply: Text detection Computer vision DL
      4. Human reviews
         1. Manage sensitive workflows
            1. Using Augmented AI
   6. Uses cases
      1. Importing documents and forms into business applications
      2. Building automated document processing workflows
      3. Extracting text for Natural Language Processing (NLP)
      4. Extracting text for document classification
      5. Maintaining compliance in document archives
      6. Creating smart search indexes
   7. Formats
      1. PNG, JPEG, TIFF, and PDF
   8. Pricing
      1. per 1000 pages in a month
         1. Detect Document Text API
         2. Analyze Document API
         3. Analyze Expense API
         4. Analyze ID API
      2. Free tier
         1. Detect Document Text API: 1,000 pages per month
         2. Analyze Expense API: 100 pages per month
         3. Analyze ID API: 100 pages per month
   9. Images / scans of docs
3. Amazon Transcribe
   1. Using Automatic Speech Recognition (ASR) technology
      1. Speech to text
         1. Audio
         2. Video
   2. Formats
      1. media files in AMR, AMR-WB, Ogg and WebM format, WAV, FLAC, MP3 or MP4
   3. Integrate
      1. Translate
         1. Language customization
      2. Polly
      3. Filter content
         1. To ensure customer privacy
      4. Amazon Transcribe with Amazon Kendra or Amazon Opensearch to index and perform text based search across audio/video library
   4. Use cases
      1. Analyze customer-agent calls
      2. Create su-titles for videos
   5. Limitations
      1. Batch
         1. 4 hours (or 2GB) per API call for our batch service
      2. Streaming
         1. open connections up to 4 hours long
   6. Benefits
      1. Custom Vocabularies
         1. Specifying lis of words
         2. Industry specific terms
         3. Spell out acronums
      2. PII redaction
         1. Identify + Redact from Transcripts
            1. Call center training
            2. Customer satisfaction
      3. Subtitles
         1. create CC
            1. video files
            2. WebVVT
            3. SubRip
      4. Vocabulary Filtering
         1. Words to eliminate form trancripts
            1. Ofensive filter Mask
            2. Generate family - friendly captions
            3. Remove proprietaty info
   7. pricing
      1. Usage is billed in one-second increments, with a minimum per request charge of 15 seconds.
      2. Free tier
         1. 60 minutes per month for 12 months
4. Amazon Comprehend
   1. Full managed
   2. Natural language processing NLP
      1. ML - Tex Info : Meaning & insights
      2. Relevant data
   3. Identify, Extract, Understand
      1. Language, Main Topics, Key phrases. Places, people, brands, events, sentiments
   4. Sources
      1. Web pages
      2. Social media feeds
      3. emails
      4. Articles
      5. Set of text docs
   5. Benefits
      1. Disvery Insights
         1. Valuable insights
            1. Customer Sentiment
            2. Voice ot hte customer
      2. Differentiate your business
         1. Train Model
            1. Classify Docs - Terms
      3. Document processing
         1. Doc proccessing workflow
            1. Text Topics Key phrases
      4. Protect access to PII
         1. Protect and Control
            1. Sensitive data PII (access, identify, Redacting)
   6. Features
      1. Language Support
         1. Text Analysis
            1. English, French, German, Italian, Portuguese, Spanish
      2. Custom Entity Recognition
         1. identify terms that are specific to your domain
            1. Private custom model (a list of policy numbers, claim numbers, or SSN)
            2. PDFs, Plain Text, MS Word docs
      3. Custom Classification
         1. build custom text classification models using your business-specific labels without learning M
      4. Sentiment Analysis
      5. Subtopic 6
      6. Comprehend Medical
5. Amazon Lex
   1. (AI) service with advanced natural language models to design, build, test, and deploy conversational interfaces
   2. Uses cases
      1. Self-service voice assistants and chatbots – build a call center bot
      2. Informational bot – build an automated customer support agent or bot that answers questions
      3. Application/Transactional bot – build a stand-alone pizza ordering agent or a travel bot
      4. Enterprise Productivity bot – build custom bots to connect to enterprise data resources
      5. Device Control bot– use Amazon Lex to issue control commands to connected devices
   3. Components
      1. Intent
         1. identify a set of actions
            1. BookTickets
      2. utterance
         1. spoken or typed phrase to invoke an intent
      3. slots
         1. needs information from the user
      4. prompts
      5. action fulfilled
6. Amazon Polly
   1. Converts Text to Speech
      1. Using DL
      2. Natural Human Speech
      3. Lifelike Speech: talkign Apps
   2. Speech Synthesis Markup Language (SSML) tags like prosody so you can adjust the speech rate, pitch, or volume
      1. W3C standard, XML-based markup language for speech synthesis applications
   3. pronunciation of particular words, such as company names, acronyms, foreign words and neologisms, e.g. “P!nk”, “ROTFL”, “C’est la vie” using custom lexicons.
   4. Multi-languages
   5. Neural TTS
      1. Adv Speech Improvement
      2. Newscaster Style
   6. Polly Brand Voice
      1. Custom voice
      2. Work with polly team
   7. File Formats
      1. MP3, Vorbis, and raw PCM audio stream formats
   8. Integration
      1. Amazon Connect, Chime SDK, AWS Contact Center Intelligenec CCI, Genesys Cloud CX,
   9. Benefits
      1. Store & redistribute
         1. Unlimited replays (no added fees)
            1. Creat3 Speech Files (MP3, OGG)
      2. Real Time Streaming
         1. Near RT
            1. MP3, Vorbis, raw PCM
      3. Custom Output
         1. SSML
            1. Phrasing
            2. Emphasis
            3. Intonation
            4. Pitch, Volume Rate
      4. Simple to use API
         1. Integrate Speech into apps return Audio send audio stream
   10. Features
       1. Speech Synchronization
          1. Send Audio Stream, Metadata Stream,
             1. Contains info: Sentences, Words, Sounds
       2. Custom Lexicons
          1. Modify pronunciation
             1. Company names, Acronyms, ROTFL Neologisms
             2. Lexical Entries
       3. Speech Synthesis
          1. API, Console, SDK
             1. AWS SDK (Java, Node.js, .NET, PHP, Python, Ruby, Go, and C++) and AWS Mobile SDK (iOS/Android).
   11. Pricing
       1. Standart
          1. You are billed monthly for the number of characters of text that you processed
       2. Free tier
          1. 5 million characters per month for speech or Speech Marks requests, for the first 12 months
7. Amazon Translate
   1. neural machine translation service customizable language translation
   2. supports translation between the following 75 languages:
   3. deep learning techniques to produce more accurate and fluent translation than traditional statistical and rule-based translation models
   4. Features
      1. Named Entity Translation Customization
      2. Language Identification
      3. Batch and Real-Time Translations
      4. Secure Machine Translation
         1. SSL encryption
   5. File Formats
      1. large number of Word documents (docx), PowerPoint presentations (pptx), Excel spreadsheets (xlsx), text, and HTML documents
   6. pricing
      1. Standart
         1. You are billed monthly for the total number of characters
      2. Free tier
         1. 500,000 characters per month for 2 months
8. Amazon Kendra
   1. Amazon Kendra is a highly scalable, intelligent enterprise search service. It uses machine learning for improved accuracy in search results and the ability to search unstructured data.
   2. Features
      1. Natural Language Processing (NLP): Amazon Kendra uses NLP to get highly accurate answers without the need for machine learning (ML) expertise.
      2. Fine-tuning Search Results: You can fine-tune your search results based on content attributes, freshness, user behavior, and more.
      3. ML-powered Instant Answers: Amazon Kendra delivers ML-powered instant answers, FAQs, and document ranking as a fully managed service.
   3. Use Cases
      1. Enhance Internal Search Experiences for Employees: Improve employee productivity and unlock the insights employees need to make data-driven business decisions through a single search interface.
      2. Improve Customer Interactions: Reduce contact center costs with intuitive self-service bots, agent-assist solutions, and frictionless document access.
      3. Integrate Search into SaaS Applications: Helps you find information faster with ML-powered in-app searches.
   4. File Formats
      1. Amazon Kendra can handle a variety of document types and formats, including PDF, HTML, Word, PowerPoint, and others.
      2. It also supports additional formats like RTF, JSON, Markdown, CSV, MS Excel, XML, and XSLT.
   5. Pricing
      1. Kendra Enterprise Edition (KEE): Provides a high-availability service for production workloads. It costs $1,008 per month.
      2. Kendra Developer Edition (KDE): Provides developers with a lower-cost option ($810 per month) to build a proof-of-concept. This edition is not recommended for production workloads.
      3. Free Tier: You can get started for free with the Amazon Kendra Developer Edition, that provides free usage of up to 750 hours for the first 30 days.
9. Amazon Forecast
   1. Amazon Forecast is a fully managed service that uses machine learning to deliver highly accurate forecasts. It is designed to harness the same technology that Amazon.com uses for its own forecasting needs.
   2. Features
      1. Data Integration: Amazon Forecast can automatically load historical time-series data from Amazon S3, or you can use the AWS Data Pipeline to import data from other sources.
      2. Automatic Data Preprocessing: The service handles data preprocessing steps like missing value imputation, outlier detection, and variable transformation.
      3. Machine Learning Algorithms: Amazon Forecast employs a range of sophisticated machine learning algorithms, including traditional statistical methods like ARIMA and more advanced deep learning algorithms like DeepAR+. The service automatically selects the best algorithm for your data, or you can specify an algorithm if you have a preference.
      4. Customizable Models: While Amazon Forecast can automatically choose an algorithm, users can also customize models based on their specific needs. This includes the ability to fine-tune parameters and incorporate additional datasets to improve forecast accuracy.
      5. Forecast Dimensions: The service supports complex forecasting scenarios, including item-level forecasting, location-based forecasting, and demand planning for multiple products or services simultaneously.
      6. Evaluation Metrics: Amazon Forecast provides metrics like Weighted Quantile Loss (wQL) to help evaluate the performance of the forecasts.
      7. Scalability and Performance: Given its cloud-based nature, Amazon Forecast can scale according to the size of the data and the complexity of the forecasting task.
      8. Easy Integration: The generated forecasts can be easily integrated into other applications or business processes through AWS SDKs and APIs.
      9. Security and Compliance: Amazon Forecast adheres to AWS’s robust security and compliance standards, ensuring that your data is protected.
10. Amazon Fraud Detector
    1. Amazon Fraud Detector is a powerful tool for businesses looking to leverage machine learning for fraud detection without needing deep expertise in the field. Its key capabilities include easy model creation, pre-built templates, real-time detection, customizable logic, risk scoring, and seamless integration with AWS services, all underpinned by Amazon's extensive experience in fraud detectio
    2. Features
       1. Machine Learning Models: Amazon Fraud Detector uses machine learning to identify potentially fraudulent activities. It leverages algorithms that have been trained on historical fraud patterns to detect anomalies and risky transactions.
       2. Easy Model Creation: Users can create a fraud detection model with just a few clicks in the AWS Management Console. The service uses your historical data to train and deploy custom fraud detection models.
       3. Pre-built Templates: Amazon Fraud Detector offers pre-built model templates based on common fraud scenarios, like online payment fraud, fake account creation, etc., which can be used to quickly deploy fraud detection models.
       4. Data Integration: The service allows for easy integration of your historical event data for model training. It can handle various types of data, including numerical, categorical, and textual.
       5. Real-time Detection: It provides real-time fraud detection, which is crucial for businesses where immediate action is required, such as e-commerce transactions.
       6. Customizable Detection Logic: Users can create custom rules to fine-tune their fraud detection strategies. This includes setting up specific conditions and thresholds to trigger alerts.
       7. Risk Scoring: Amazon Fraud Detector assigns risk scores to transactions or activities, which helps in determining the level of risk and the appropriate action to take.
       8. Batch Import and Export: In addition to real-time analysis, it supports batch import and export of data for offline analysis and model retraining.
       9. Integration with Other AWS Services: It can be easily integrated with other AWS services like Amazon S3, AWS Lambda, and Amazon SageMaker for extended functionality.
       10. Security and Compliance: As part of AWS, it adheres to strict security standards, ensuring the confidentiality and integrity of your data.
       11. Global Reach: Leveraging AWS infrastructure, it can be deployed globally, enabling businesses to implement consistent fraud detection strategies across different regions.
       12. API Access: Amazon Fraud Detector provides APIs for easy integration with your applications, allowing for automated fraud checks within existing systems.
11. Amazon SageMaker
    1. A fully managed service that allows data scientists and developers to easily build, train, and deploy machine learning models at scale.
    2. Features
       1. SageMaker AutoPilot – automates the process of building, tuning, and deploying machine learning models based on a tabular dataset (CSV or Parquet). SageMaker Autopilot automatically explores different solutions to find the best model.
       2. SageMaker GroundTruth – a data labeling service that lets you use workforce (human annotators) through your own private annotators, Amazon Mechanical Turk, or third-party services.
       3. SageMaker Data Wrangler – a visual data preparation and cleaning tool that allows data scientists and engineers to easily clean and prepare data for machine learning.
       4. SageMaker Neo – allows you to optimize machine learning models for deployment on edge devices to run faster with no loss in accuracy.
       5. SageMaker Automatic Model Tuning – automates the process of hyperparameter tuning based on the algorithm and hyperparameter ranges you specify. This can result in saving a significant amount of time for data scientists and engineers.
       6. Amazon SageMaker Debugger – provides real-time insights into the training process of machine learning models, enabling rapid iteration. It allows you to monitor and debug training issues, optimize model performance, and improve overall accuracy by analyzing various model-related metrics, such as weights, gradients, and biases.
       7. Managed Spot Training – allows data scientists and engineers to save up to 90% on the cost of training machine learning models by using spare compute capacity.
       8. Distributed Training – allows for splitting the data and distributing the workload across multiple instances, improving speed and performance. It supports various distributed training frameworks such as TensorFlow, PyTorch, and MXNet.
12. Amazon Bedrock
    1. Amazon Bedrock is a fully managed service that allows you to build and scale generative AI applications. These applications can generate text, images, audio, and synthetic data in response to prompts
    2. Features
       1. Model Choice: Amazon Bedrock provides access to a variety of high-performing foundation models from leading AI companies such as AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon. You can easily experiment with and evaluate these models for your use case.
       2. Customization: You can privately customize the models with your data using techniques such as fine-tuning and Retrieval Augmented Generation (RAG).
       3. Agents: You can build agents that execute tasks using your enterprise systems and data sources.
       4. Serverless: Since Amazon Bedrock is serverless, you don’t have to manage any infrastructure.
       5. Integration: You can securely integrate and deploy generative AI capabilities into your applications using the AWS services you are already familiar with.
       6. Knowledge base for Amazon Bedrock: The knowledge base for Amazon Bedrock provides the capability of amassing data sources into a repository of information. With knowledge bases, you can easily build an application that takes advantage of retrieval augmented generation (RAG), a technique in which the retrieval of information from data sources augments the generation of model responses.
       7. Text, Image, and Chat playgrounds: Amazon Bedrock provides playgrounds for text, chat, and image models. In these playgrounds, you can experiment with models before deciding to use them in an application
       8. Embeddings: Amazon Bedrock provides text and image embeddings that represent meaningful vector representations of unstructured text, such as documents, paragraphs, and sentences.
       9. Fine-tuning and Continued Pre-training: Amazon Bedrock provides a new capability that allows you to train Amazon Titan Text Express and Amazon Titan Text Lite foundation models and customize them using your own unlabeled data in a secure and managed environment.