[PYTHON] Summary of recommended APIs for artificial intelligence, machine learning, and AI

Watson API Provided by: IBM Link: https://www.ibm.com/watson/jp-ja/developercloud/services-catalog.html Functions: Search, Text Analysis, Image Recognition, Speech Recognition, Speech Reading, Translation, Psychological Analysis, Sentiment Analysis, Data Analysis Platform

Vision AI Provided by: Google Link: https://cloud.google.com/vision/ Function: Analyze images in the cloud or on the edge

Cloud Speech-to-Text API Provided by: Google Link: https://cloud.google.com/speech-to-text/ Function: Convert voice to text by machine learning, support short-time voice and long-time voice

Cloud AutoML Provided by: Google Link: https://cloud.google.com/automl/ Features: Quick and easy training of custom ML models

dialogflow Provided by: Google Link: https://dialogflow.com/ Function: API that responds to reservations / orders from customers and inquiries with a natural language processor (chatbot)

Wit Courtesy: Wit.ai Link: https://wit.ai/ Function: Natural language processing

AWS Machine Learning

Provided by: AWS Link: https://aws.amazon.com/jp/machine-learning/ Features: Speech, Advanced Text Analysis, Document Analysis, Translation, Transcription, Interactive Agent

reference

http://smsurf.app-rox.com/api/

Recommended Posts

Summary of recommended APIs for artificial intelligence, machine learning, and AI
[For beginners of artificial intelligence] Machine learning / Deep Learning Programming Learning path and reference books
Summary of mathematical scope and learning resources required for machine learning and data science
[Recommended tagging for machine learning # 2.5] Modification of scraping script
Artificial intelligence, machine learning, deep learning to implement and understand
Machine learning ③ Summary of decision tree
[Recommended tagging for machine learning # 4] Machine learning script ...?
First Steps for Machine Learning (AI) Beginners
2020 Recommended 20 selections of introductory machine learning books
Machine learning algorithm classification and implementation summary
How to use machine learning for work? 02_Overview of AI development project
[Summary of books and online courses used for programming and data science learning]
Beginning of machine learning (recommended teaching materials / information)
Recommended study order for machine learning / deep learning beginners
Numerai Tournament-Fusion of Traditional Quants and Machine Learning-
Summary of evaluation functions used in machine learning
(Updated from time to time) Summary of machine learning APIs that allow you to quickly build apps by Team AI
Machine learning tutorial summary
Machine learning ⑤ AdaBoost Summary
Python learning memo for machine learning by Chainer Chapters 1 and 2
Machine learning engineer lawyer explains AI and rights story
Summary of the basic flow of machine learning with Python
Summary for learning RAPIDS
Summary of know-how and tips for AI new business planning that AI engineers want to know
Performance verification of data preprocessing for machine learning (numerical data) (Part 2)
What I learned about AI and machine learning using Python (4)
Site summary where you can learn machine learning for free
A beginner's summary of Python machine learning is super concise.
Performance verification of data preprocessing for machine learning (numerical data) (Part 1)
Data set for machine learning
Japanese preprocessing for machine learning
Basics of Machine Learning (Notes)
Python learning plan for AI learning
Machine learning ② Naive Bayes Summary
Machine learning article summary (self-authored)
Importance of machine learning datasets
Machine learning and mathematical optimization
Machine learning ④ K-nearest neighbor Summary
[Python machine learning] Recommendation of using Spyder for beginners (as of August 2020)
Creating artificial intelligence by machine learning using TensorFlow from zero knowledge-Introduction 1
How to use machine learning for work? 01_ Understand the purpose of machine learning
Summary of pages useful for studying the deep learning framework Chainer
[For beginners] Summary of suffering from kaggle's EDA and its struggle
Feature engineering for machine learning starting with the 1st Google Colaboratory --Binarization and discretization of count data
Machine learning summary by Python beginners
Classification and regression in machine learning
<For beginners> python library <For machine learning>
Organize machine learning and deep learning platforms
A Tour of Go Learning Summary
Machine learning meeting information for HRTech
[For competition professionals] Summary of doubling
Summary of Python indexes and slices
[AI] Deep Learning for Image Denoising
An introductory reader of machine learning theory for IT engineers tried Kaggle
A collection of tips for speeding up learning and reasoning with PyTorch
[Example of Python improvement] What is the recommended learning site for Python beginners?
Python learning memo for machine learning by Chainer Chapter 13 Basics of neural networks
Basic machine learning procedure: ③ Compare and examine the selection method of features
Python learning memo for machine learning by Chainer until the end of Chapter 2
Python: Preprocessing in machine learning: Handling of missing, outlier, and imbalanced data
School service (free / paid) where you can learn programming language Python and artificial intelligence technology (machine learning / deep learning)