I had a look at our current docs and found gaps in the Algorithm documentations between the AWS dev guide and readthedocs.io.
The AWS dev guide lists all algos that are officially released (left column below), but some of them are not documented in readthedocs.io (right column below).
AWS dev guide
pySDK in First-Party Algorithms
BlazingText
(missing)
DeepAR Forecasting
(missing)
Factorization Machines
FactorizationMachines
Image Classification Algorithm
(missing)
IP Insights
IP Insights
K-Means Algorithm
K-means
K-Nearest Neighbors (k-NN) Algorithm
K-Nearest Neighbors
Latent Dirichlet Allocation (LDA)
LDA
Linear learner algorithm
LinearLearner
Neural Topic Model (NTM) Algorithm
NTM
Object2Vec
Object2Vec
Object Detection Algorithm
(missing)
Principal Component Analysis (PCA) Algorithm
PCA
Random Cut Forest (RCF) Algorithm
Random Cut Forest
Semantic Segmentation
(missing)
Sequence to Sequence (seq2seq)
(missing)
XGBoost
XGBoost (is under the Framework node)
In case of XGBoost, I suggest to list it with the other algos and provide a link to the exisiting XGBoost in the Framework node with a short explanation of why XGBoost is under Frameworks.
Describe how documentation can be improved
Add the 6 missing algorithms to the readthedoc.io 1p algorithm section.
Add XGBoost to the 1p algorithm section as well, and link to the existing XGBoost documentation under the Frameworks node.
What did you find confusing? Please describe.
I had a look at our current docs and found gaps in the Algorithm documentations between the AWS dev guide and readthedocs.io.
The AWS dev guide lists all algos that are officially released (left column below), but some of them are not documented in readthedocs.io (right column below).
In case of XGBoost, I suggest to list it with the other algos and provide a link to the exisiting XGBoost in the Framework node with a short explanation of why XGBoost is under Frameworks.
Describe how documentation can be improved