AI / Machine Learning
The AI
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how to get into
ai and machine learning
- Predictive analysis
- Data warehousing
- Data Pipelines
- ML for Marketing
- Documents Classification
- Social Analytics
- Sentiment Analysis
- Natural Language Understanding
- Image Classification
- Object Detection
- Text to Image
- Semantic Segmentation
Big Data Analytics
Get insight and prediction from data
Big data is the fundamental consequence of the new marketing landscape. The data can help you discover hidden patterns such as the way different groups of customers interact and how this leads to purchase decisions. Equipped with these insights, companies can then develop targeted marketing campaigns that cater to the customer’s individual preferences.
Text Analytics
extract and classify information from text
Text analysis allows companies to automatically extract and classify information from text, such as social media platform, emails, documents, support tickets, invoice, or survey responses. Popular advanced techniques include sentiment analysis, topic detection, and keyword extraction.
Social analytics/listening is one of the most critical customer service practices by using text analytics. This technique helps to extract specific information, like keywords, names, or company information. They may even want to categorize text with tags according to topic or viewpoint or classify it as positive or negative. You can gather the information and get feedback about your company from blogs and social media sites and analyzing it to help make business decisions.
Computer Vision
train computers to read visual effects
Computer vision is an AI model that trains computers to interpret and understand visual effects. By Using digital images, videos and deep learning models, the machines can accurately identify, classify, detect, clustering the objects and face recognition. It can also transfer the image into the texts and vice verse.
Computer vision can be used across industries to enhance the consumer experience, reduce costs and increase security.
For example. In manufacturing, businesses use computer vision to identify product defects in real time. As the products are coming off the production line, a computer processes images or videos, and flags dozens of different types of defects — even on the smallest of products.
A good place to start with
AI / ML Components in
GOOGLE CLOUD PLATFORM
DataQuery
BigQuery is a serverless, highly-scalable, and cost-effective cloud data warehouse with an in-memory BI Engine and AI Platform built in.
Cloud BigTable
A petabyte-scale, fully managed NoSQL database service for large analytical and operational workloads.
Cloud Pub/Sub
Ingest events at any scale,Simplify development of event-driven micro services.
Cloud Storage
Unified object storage for developers and enterprises. You can choose your location type based on redundancy and performance needs.
Cloud Dataprep
An intelligent cloud data service to visually explore, clean, and prepare data for analysis and machine learning.
Cloud Composer
A fully managed workflow orchestration service built on Apache Airflow.
AI Platform
Create your AI applications once, then run them easily on both GCP and on-premises. Take your machine learning projects to production.
Cloud AutoML
Train high-quality custom machine learning models with minimal effort and machine learning expertise.
