Install
Gluon
About
Dive into Deep Learning
GluonCV Toolkit
GluonNLP Toolkit
API
Python
C++
Clojure
Java
Julia
Perl
R
Scala
Docs
FAQ
Tutorials
Examples
Architecture
Developer Wiki
Model Zoo
ONNX
Community
Forum
Github
Contribute
Ecosystem
Powered By
1.4.1
master
1.7.0
1.6.0
1.5.0
1.4.1
1.3.1
1.2.1
1.1.0
1.0.0
0.12.1
0.11.0
☰
Install
Tutorials
Gluon
About
The Straight Dope (Tutorials)
GluonCV Toolkit
GluonNLP Toolkit
API
Python
C++
Clojure
Java
Julia
Perl
R
Scala
Docs
FAQ
Tutorials
Examples
Architecture
Developer Wiki
Gluon Model Zoo
ONNX
Community
Forum
Github
Contribute
Ecosystem
Powered By
1.4.1
master
1.6.0
1.5.0
1.4.1
1.3.1
1.2.1
1.1.0
1.0.0
0.12.1
0.11.0
MXNet APIs
MXNet Architecture
MXNet Community
MXNet FAQ
About Gluon
Installing MXNet
Nvidia Jetson TX family
Source Download
MXNet Model Zoo
Tutorials
Tutorials
¶
Iterators - Loading data
Prerequisites
MXNet Data Iterator
Reading data in memory
Reading data from CSV files
Custom Iterator
Record IO
MXRecordIO
MXIndexedRecordIO
Packing and Unpacking data
Packing/Unpacking Binary Data
Packing/Unpacking Image Data
Using tools/im2rec.py
Image IO
Preprocessing Images
Loading raw images
Image Transformations
Loading Data using Image Iterators
Using ImageRecordIter
Using ImageIter
Module - Neural network training and inference
Prerequisites
Preliminary
Creating a Module
Intermediate-level Interface
High-level Interface
Train
Predict and Evaluate
Save and Load
NDArray - Imperative tensor operations on CPU/GPU
Prerequisites
Array Creation
Printing Arrays
Basic Operations
Indexing and Slicing
Shape Manipulation
Reduce
Broadcast
Copies
Advanced Topics
GPU Support
Serialize From/To (Distributed) Filesystems
Lazy Evaluation and Automatic Parallelization
NDArray Indexing - Array indexing features
Basic Slicing and Indexing
New Indexing Features in v1.0
Step
Negative Indices
New Advanced Indexing Features in v1.0
Purely Integer Array Indexing
Combining Advanced and Basic Indexing
References
Symbol - Neural network graphs
Prerequisites
Basic Symbol Composition
Basic Operators
Basic Neural Networks
More Complicated Composition
Modularized Construction for Deep Networks
Group Multiple Symbols
Relations to NDArray
Symbol Manipulation
Shape and Type Inference
Bind with Data and Evaluate
Load and Save
Customized Symbol
Advanced Usages
Type Cast
Variable Sharing