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Course Outline
Getting Started
- Quickstart: Running Examples and DL4J in Your Projects
- Comprehensive Setup Guide
Introduction to Neural Networks
- Restricted Boltzmann Machines
- Convolutional Nets (ConvNets)
- Long Short-Term Memory Units (LSTMs)
- Denoising Autoencoders
- Recurrent Nets and LSTMs
Multilayer Neural Nets
- Deep-Belief Network
- Deep AutoEncoder
- Stacked Denoising Autoencoders
Tutorials
- Using Recurrent Nets in DL4J
- MNIST DBN Tutorial
- Iris Flower Tutorial
- Canova: Vectorization Lib for ML Tools
- Neural Net Updaters: SGD, Adam, Adagrad, Adadelta, RMSProp
Datasets
- Datasets and Machine Learning
- Custom Datasets
- CSV Data Uploads
Scaleout
- Iterative Reduce Defined
- Multiprocessor / Clustering
- Running Worker Nodes
Text
- DL4J's NLP Framework
- Word2vec for Java and Scala
- Textual Analysis and DL
- Bag of Words
- Sentence and Document Segmentation
- Tokenization
- Vocab Cache
Advanced DL2J
- Build Locally From Master
- Contribute to DL4J (Developer Guide)
- Choose a Neural Net
- Use the Maven Build Tool
- Vectorize Data With Canova
- Build a Data Pipeline
- Run Benchmarks
- Configure DL4J in Ivy, Gradle, SBT etc
- Find a DL4J Class or Method
- Save and Load Models
- Interpret Neural Net Output
- Visualize Data with t-SNE
- Swap CPUs for GPUs
- Customize an Image Pipeline
- Perform Regression With Neural Nets
- Troubleshoot Training & Select Network Hyperparameters
- Visualize, Monitor and Debug Network Learning
- Speed Up Spark With Native Binaries
- Build a Recommendation Engine With DL4J
- Use Recurrent Networks in DL4J
- Build Complex Network Architectures with Computation Graph
- Train Networks using Early Stopping
- Download Snapshots With Maven
- Customize a Loss Function
Requirements
Knowledge in the following:
- Java
Testimonials
It was very interactive and more relaxed and informal than expected. We covered lots of topics in the time and the trainer was always receptive to talking more in detail or more generally about the topics and how they were related. I feel the training has given me the tools to continue learning as opposed to it being a one off session where learning stops once you've finished which is very important given the scale and complexity of the topic.
Jonathan Blease
The topic is very interesting.
Wojciech Baranowski
Trainers theoretical knowledge and willingness to solve the problems with the participants after the training.
Grzegorz Mianowski
Topic. Very interesting!.
Piotr
Exercises after each topic were really helpful, despite there were too complicated at the end. In general, the presented material was very interesting and involving! Exercises with image recognition were great.
Dolby Poland Sp. z o.o.
I think that if training would be done in polish it would allow the trainer to share his knowledge more efficient.
Radek
The global overview of deep learning.
Bruno Charbonnier
The exercises are sufficiently practical and do not need high knowledge in Python to be done.
Alexandre GIRARD
Doing exercises on real examples using Eras. Italy totally understood our expectations about this training.
Paul Kassis
We have gotten a lot more insight in to the subject matter. Some nice discussion were made with some real subjects within our company.
Sebastiaan Holman
The training provided the right foundation that allows us to further to expand on, by showing how theory and practice go hand in hand. It actually got me more interested in the subject than I was before.
Jean-Paul van Tillo
I really enjoyed the coverage and depth of topics.
Anirban Basu
The deep knowledge of the trainer about the topic.
Sebastian Görg
way of conducting and example given by the trainer
ORANGE POLSKA S.A.
Possibility to discuss the proposed issues yourself
ORANGE POLSKA S.A.
Communication with lecturers
文欣 张
like it all
lisa xie
In-depth coverage of machine learning topics, particularly neural networks. Demystified a lot of the topic.
Sacha Nandlall
Big and up-to-date knowledge of leading and practical application examples.
- ING Bank Śląski S.A.
A lot of exercises, very good cooperation with the group.
Janusz Chrobot - ING Bank Śląski S.A.
work on colaborators,
- ING Bank Śląski S.A.
It was obvious that the enthusiasts of the presented topics were leading. Used interesting examples during exercise.
- ING Bank Śląski S.A.
I was benefit from the passion to teach and focusing on making thing sensible.
Zaher Sharifi - GOSI
The informal exchanges we had during the lectures really helped me deepen my understanding of the subject
- Explore
lots of information, all questions ansered, interesting examples
A1 Telekom Austria AG
having access to the notebooks to work through
Premier Partnership
The trainers knowledge of the topics he was teaching.
Premier Partnership
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