Machine
Learning
Unsupervised
Learning
Supervised
Learning
Reinforced
Learning
Unsupervised
Learning
Clustering
Dimensionality Reduction
Targeted
Marketing
Recommender Systems
Customer Segmentation
Meaningful
Compression
Structure
Discovery
Feature
Elicitation
Big Data Visualizations
Supervised
Learning
Classification
Prediction
Image Classification
Fraud Detection
Customer Retention
Diagnostics
Natural Language Processing
Advertising Popularity Prediction
Weather Forecast
Marketing Forecast
Life Length Prediction
Population Growth Prediction
Reinforced
Learning
Optimisation
Aircraft Wing Modeling
Game AI
Real Time Decisions
Skill
Acquisition
Learning Tasks
Robot Navigation
PCB Layouting
Catalogue Planning
Warning: Especially in ML topics clients have only rough idea what they want. Often no idea at all.
Communication is key. Guide them through the options what is possible.
Ask about their systems and technologies. How you will get the data?
A quick exploration using AutoML is good start.
Formalize requirements and agree on budget.
Never promise high accruacy!
The most critical part to build client's confidence in you.
Try to get direct contacts to people who understand business. Avoid mediators if possible.
Python is a great tool for prototyping
Explore data.
Understand visualizations available.
This is also something you can sell to your client. Often it can bring him high value.
Data
Classification
GA
GA
Prediction
Infrastructure
Visualizations
Dashboards
Use Case UI
Visualizations
Backoffice
APIs
APIs
Orchestrations
Scaling
Aggregation
Data Science
Frontend
FE for BE
Backend
or use Websockets