This post consist of the notes that are based on the series of AWS SageMaker videos provided by Amazon Web Services Amazon SageMaker Technical Deep Dive Series.

Fully-Managed Notebook Instances with Amazon SageMaker

Create your Notebook Instance:

Pick the right family:
- t - tiny < m, c - computed optimized, p - GPU
Pick the right size:
- From medium to very very large.
Pick the right version:
- ml.t3.medium: 3 means the latest version in the T family

There are ~200 example notebooks in SageMaker Notebook, definitely try them out.

Built-in Machine Learning Algorithms with Amazon SageMaker

** = Distributed Training*

<> = incremental training

Type of Problem	Algorithms
Classification	Linear Learner *XGBoostKNNFatorization Machines
Computer Vision	Image Classification <>Object DetectionSemantic Segmentation
Topic Modeling	LDANTM
Working with Text	Blazing Text- Supervised- Unsupervised *
Recommendation	Fatorization Machines * (+ KNN)
Forecasting	DeepAR *
Anomaly Detection	Random Cut Forests IP Insights
Clustering	KMeans *KNN
Sequence Translation	Seq2Seq *
Regression	Linear LearnerXGBoostKNN
Feature Reduction	PCA Object2Vec