AI Cheat Sheet¶

Introduction¶

Welcome to this AI Cheat Sheet! Whether you're an AI transformation consultant, a web entrepreneur like Mat, or someone keen on diving into the world of Artificial Intelligence, this guide aims to be your go-to reference.

TOC¶

AI Cheat Sheet

What's Inside?¶

Machine Learning Algorithms: A rundown of popular algorithms in supervised, unsupervised, and reinforcement learning.
Data Preprocessing: Essential steps to prepare your data for AI algorithms, because garbage in equals garbage out!
Common Libraries: A list of must-know libraries and frameworks that make your life easier in implementing AI solutions.
Cloud AI Services: An overview of AI services offered by popular cloud providers, saving you the hassle of building models from scratch.
Quick Commands: Short code snippets for when you need to quickly look up how to do something.

Who Is This For?¶

AI Consultants: Understand the key algorithms and tools at a glance.
Web Entrepreneurs: Quickly look up how to implement AI features into your applications.
Data Enthusiasts: Know the preprocessing steps to get your data ready for machine learning models.
Tech Stack Experts: If you're familiar with stacks like MongoDB, FastAPI, and AWS EC2 instances, you'll find this cheat sheet complementary to your existing knowledge base.

How to Use This Cheat Sheet¶

Quick Reference: Keep this cheat sheet handy for a quick recap of essential AI concepts and commands.
Project Planning: Use it as a guide to decide on the algorithms or services to use for your next AI project.
Learning: If you're new to AI, this cheat sheet can serve as a roadmap of what to learn.

Machine Learning Algorithms¶

Supervised Learning
Linear Regression
Logistic Regression
Decision Trees
Random Forest
Unsupervised Learning
K-Means
Hierarchical Clustering
PCA
Reinforcement Learning
Q-Learning
SARSA

Data Preprocessing¶

Data Cleaning
Handle missing values
Remove duplicates
Feature Engineering
One-hot encoding
Normalization
Data Split
Training set
Test set
Validation set

Common Libraries¶

Python Libraries
Scikit-learn
TensorFlow
PyTorch
JavaScript Libraries
TensorFlow.js
Synaptic.js

Cloud AI Services¶

AWS
SageMaker
Comprehend
Google Cloud
AutoML
Natural Language API
Azure
Machine Learning Studio
Cognitive Services

Quick Commands¶

Scikit-learn python from sklearn.model_selection import train_test_split
TensorFlow python model = tf.keras.Sequential()
PyTorch python import torch.nn as nn