Deep Learning for Finance (with R)

  28 hours

Deep Learning for Banking (with Python)

  28 hours

Deep Learning for Banking (with R)

  28 hours

Deep Learning for Finance (with Python)

  28 hours

Matlab for Deep Learning

  14 hours

Artificial Neural Networks, Machine Learning, Deep Thinking

  21 hours

Introduction Deep Learning and Neural Network for Engineers

  21 hours

Microsoft Cognitive Toolkit 2.x

  21 hours

Deep Reinforcement Learning with Python

  21 hours

Neural computing – Data science

  14 hours

Advanced Machine Learning with Python

  21 hours

Advanced Machine Learning with R

  21 hours

Amazon DSSTNE: Build a Recommendation System

  7 hours

Introduction to Deep Learning

  21 hours

Advanced Deep Learning

  28 hours

Machine Learning and Deep Learning

  21 hours

T2T: Creating Sequence to Sequence Models for Generalized Learning

  7 hours

Deep Learning AI Techniques for Executives, Developers and Managers

  21 hours

Deep Learning for Medicine

  14 hours

Deep Learning for Healthcare

  14 hours

Deep Learning for Business

  14 hours

TensorFlow Lite for Android

  21 hours

TensorFlow Lite for iOS

  21 hours

TensorFlow Lite for Embedded Linux

  21 hours

Tensorflow Lite for Microcontrollers

  21 hours

Torch for Machine and Deep Learning

  21 hours

Artificial Intelligence in Automotive

  14 hours

Neural Networks Fundamentals using TensorFlow as Example

  28 hours

TPU Programming: Building Neural Network Applications on Tensor Processing Units

  7 hours

Understanding Deep Neural Networks

  35 hours

Applied AI from Scratch

  28 hours

Natural Language Processing with TensorFlow

  35 hours

Deep Learning for NLP (Natural Language Processing)

  28 hours

Fraud Detection with Python and TensorFlow

  14 hours

Deep Learning for Vision

  21 hours

Deep Learning with TensorFlow

  21 hours

PaddlePaddle

  21 hours

Deep Learning Neural Networks with Chainer

  14 hours

NLP with Deeplearning4j

  14 hours

Mastering Deeplearning4j

  21 hours

DeepLearning4J for Image Recognition

  21 hours

Deep Learning for Telecom (with Python)

  28 hours

Advanced Deep Learning with Keras and Python

  14 hours

Deep Learning for Self Driving Cars

  21 hours

Deep Learning with Keras

  21 hours

Python and Deep Learning with OpenCV 4

  14 hours

Deep Learning for Vision with Caffe

  21 hours

OpenNN: Implementing Neural Networks

  14 hours

OpenNMT: Setting Up a Neural Machine Translation System

  7 hours

Facebook NMT: Setting up a Neural Machine Translation System

  7 hours

OpenFace: Creating Facial Recognition Systems

  14 hours

Hardware-Accelerated Video Analytics

  14 hours

Embedding Projector: Visualizing Your Training Data

  14 hours

Kubeflow on OpenShift

  28 hours

Mastering Apache SINGA

  21 hours

Building Deep Learning Models with Apache MXNet

  21 hours

Accelerating Deep Learning with FPGA and OpenVINO

  35 hours

Distributed Deep Learning with Horovod

  7 hours

AlphaFold

  7 hours

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 [Artificial Neural Networks, Machine Learning, Deep Thinking]

The topic is very interesting.

Wojciech Baranowski [Introduction to Deep Learning]

Trainers theoretical knowledge and willingness to solve the problems with the participants after the training.

Grzegorz Mianowski [Introduction to Deep Learning]

Topic. Very interesting!.

Piotr [Introduction to Deep Learning]

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. [Introduction to Deep Learning]

I think that if training would be done in polish it would allow the trainer to share his knowledge more efficient.

Radek [Introduction to Deep Learning]

The global overview of deep learning.

Bruno Charbonnier [Advanced Deep Learning]

The exercises are sufficiently practical and do not need high knowledge in Python to be done.

Alexandre GIRARD [Advanced Deep Learning]

Doing exercises on real examples using Eras. Italy totally understood our expectations about this training.

Paul Kassis [Advanced Deep Learning]

I really appreciated the crystal clear answers of Chris to our questions.

Léo Dubus [Réseau de Neurones, les Fondamentaux en utilisant TensorFlow comme Exemple]

I generally enjoyed the knowledgeable trainer.

Sridhar Voorakkara [Neural Networks Fundamentals using TensorFlow as Example]

I was amazed at the standard of this class - I would say that it was university standard.

David Relihan [Neural Networks Fundamentals using TensorFlow as Example]

Very good all round overview. Good background into why Tensorflow operates as it does.

Kieran Conboy [Neural Networks Fundamentals using TensorFlow as Example]

I liked the opportunities to ask questions and get more in depth explanations of the theory.

Sharon Ruane [Neural Networks Fundamentals using TensorFlow as Example]

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 [Machine Learning and Deep Learning]

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 [Machine Learning and Deep Learning]

I really enjoyed the coverage and depth of topics.

Anirban Basu [Machine Learning and Deep Learning]

The deep knowledge of the trainer about the topic.

Sebastian Görg [Introduction to Deep Learning]

Very updated approach or CPI (tensor flow, era, learn) to do machine learning.

Paul Lee [TensorFlow for Image Recognition]

Given outlook of the technology: what technology/process might become more important in the future; see, what the technology can be used for.

Commerzbank AG [Neural Networks Fundamentals using TensorFlow as Example]

I was benefit from topic selection. Style of training. Practice orientation.

Commerzbank AG [Neural Networks Fundamentals using TensorFlow as Example]

way of conducting and example given by the trainer

ORANGE POLSKA S.A. [Machine Learning and Deep Learning]

Possibility to discuss the proposed issues yourself

ORANGE POLSKA S.A. [Machine Learning and Deep Learning]

Communication with lecturers

文欣 张 [Artificial Neural Networks, Machine Learning, Deep Thinking]

like it all

lisa xie [Artificial Neural Networks, Machine Learning, Deep Thinking]

In-depth coverage of machine learning topics, particularly neural networks. Demystified a lot of the topic.

Sacha Nandlall [Python for Advanced Machine Learning]

Big and up-to-date knowledge of leading and practical application examples.

- ING Bank Śląski S.A. [Introduction to Deep Learning]

A lot of exercises, very good cooperation with the group.

Janusz Chrobot - ING Bank Śląski S.A. [Introduction to Deep Learning]

work on colaborators,

- ING Bank Śląski S.A. [Introduction to Deep Learning]

It was obvious that the enthusiasts of the presented topics were leading. Used interesting examples during exercise.

- ING Bank Śląski S.A. [Introduction to Deep Learning]

A wide range of topics covered and substantial knowledge of the leaders.

- ING Bank Śląski S.A.; Kamil Kurek Programowanie [Understanding Deep Neural Networks]

Lack

- ING Bank Śląski S.A.; Kamil Kurek Programowanie [Understanding Deep Neural Networks]

Big theoretical and practical knowledge of the lecturers. Communicativeness of trainers. During the course, you could ask questions and get satisfactory answers.

Kamil Kurek - ING Bank Śląski S.A.; Kamil Kurek Programowanie [Understanding Deep Neural Networks]

Practical part, where we implemented algorithms. This allowed for a better understanding of the topic.

- ING Bank Śląski S.A.; Kamil Kurek Programowanie [Understanding Deep Neural Networks]

exercises and examples implemented on them

Paweł Orzechowski - ING Bank Śląski S.A.; Kamil Kurek Programowanie [Understanding Deep Neural Networks]

Examples and issues discussed.

- ING Bank Śląski S.A.; Kamil Kurek Programowanie [Understanding Deep Neural Networks]

Substantive knowledge, commitment, a passionate way of transferring knowledge. Practical examples after a theoretical lecture.

Janusz Chrobot - ING Bank Śląski S.A.; Kamil Kurek Programowanie [Understanding Deep Neural Networks]

Practical exercises prepared by Mr. Maciej

- ING Bank Śląski S.A.; Kamil Kurek Programowanie [Understanding Deep Neural Networks]

I was benefit from the passion to teach and focusing on making thing sensible.

Zaher Sharifi - GOSI [Advanced Deep Learning]

Human identification and circuit board bad point detection

王 春柱 - 中移物联网 [Deep Learning for NLP (Natural Language Processing)]

Demonstrate

- 中移物联网 [Deep Learning for NLP (Natural Language Processing)]

About face area.

- 中移物联网 [Deep Learning for NLP (Natural Language Processing)]

The informal exchanges we had during the lectures really helped me deepen my understanding of the subject

- Explore [Deep Reinforcement Learning with Python]

A lot of practical tips

Pawel Dawidowski - ABB Sp. z o.o. [Deep Learning with TensorFlow]

A lot of information related to the implementation of solutions

Michał Smolana - ABB Sp. z o.o. [Deep Learning with TensorFlow]

A multitude of practical tips and knowledge of the lecturer from a wide range of AI / IT / SQL / IoT issues.

- ABB Sp. z o.o. [Deep Learning with TensorFlow]

lots of information, all questions ansered, interesting examples

A1 Telekom Austria AG [Deep Learning for Telecom (with Python)]

I started with close to zero knowledge, and by the end I was able to build and train my own networks.

Huawei Technologies Duesseldorf GmbH [TensorFlow for Image Recognition]

Organization, adhering to the proposed agenda, the trainer's vast knowledge in this subject

Ali Kattan - TWPI [Natural Language Processing with TensorFlow]

the way he present everything with examples and training was so useful

Ibrahim Mohammedameen - TWPI [Natural Language Processing with TensorFlow]

Very knowledgeable

Usama Adam - TWPI [Natural Language Processing with TensorFlow]

The excersise where we should train a network to approximate a function

Nercia Utbildning AB [Deep Learning with TensorFlow 2.0]

Tomasz really know the information well and the course was well paced.

Raju Krishnamurthy - Google [TensorFlow Extended (TFX)]

having access to the notebooks to work through

Premier Partnership [Python for Advanced Machine Learning]

The trainers knowledge of the topics he was teaching.

Premier Partnership [Python for Advanced Machine Learning]

The trainer explained the content well and was engaging throughout. He stopped to ask questions and let us come to our own solutions in some practical sessions. He also tailored the course well for our needs.

Robert Baker [Deep Learning with TensorFlow 2.0]

Trainer was very knowledgeable and open to questions, liked to draw diagrams and explained things in a pretty good way

  [Deep Learning with TensorFlow 2.0]

Trainer was very knowledgeable and open to questions, liked to draw diagrams and explained things in a pretty good way

  [Deep Learning with TensorFlow 2.0]





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