SC, Charleston - Faber Center
SC, Charleston - Meeting Street
Subcategories (11)
Explore Our Courses
Edge AI for Financial Services
14 HoursEdge AI in Industrial Automation
14 HoursLightGBM for Machine Learning
21 HoursAlphaFold
7 HoursEdge AI with TensorFlow Lite
14 HoursData Mining with Weka
14 HoursAdvanced Analytics with RapidMiner
14 HoursDeepSpeed for Deep Learning
21 HoursVertex AI
7 HoursApplied AI from Scratch in Python
28 HoursH2O AutoML
14 HoursAutoML with Auto-sklearn
14 HoursAutoML with Auto-Keras
14 HoursTensorFlow Lite for Embedded Linux
21 HoursTensorFlow Lite for Android
21 HoursTensorFlow Lite for iOS
21 HoursTensorflow Lite for Microcontrollers
21 HoursDeep Learning with Keras
21 HoursDeep Learning for Self Driving Cars
21 HoursTorch for Machine and Deep Learning
21 HoursDeep Learning for Vision with Caffe
21 HoursMastering Apache SINGA
21 HoursMastering Deeplearning4j
21 HoursNLP with Deeplearning4j
14 HoursApplied AI from Scratch
28 HoursDeep Learning for Vision
21 HoursKubeflow on OpenShift
28 HoursDeep Learning with TensorFlow 2
21 HoursMachine Learning with TensorFlow.js
14 HoursTensorFlow Serving
7 HoursDeep Learning with TensorFlow
21 HoursTensorFlow for Image Recognition
28 HoursTensorFlow Extended (TFX)
21 HoursUnderstanding Deep Neural Networks
35 HoursAdaBoost Python for Machine Learning
14 HoursMachine Learning with Random Forest
14 HoursDataRobot
7 HoursAutoML
14 HoursGoogle Cloud AutoML
7 HoursPattern Recognition
21 HoursPattern Matching
14 HoursMachine Learning with PredictionIO
21 HoursIntroduction to Deep Learning
21 HoursAdvanced Deep Learning
28 HoursDeep Learning for Business
14 HoursDeep Learning for Finance (with R)
28 HoursDeep Learning for Banking (with R)
28 HoursDeep Learning for Medicine
14 HoursDeep Learning for Healthcare
14 HoursMatlab for Deep Learning
14 HoursMachine Learning and Deep Learning
21 HoursNeural computing – Data science
14 HoursOpenNN: Implementing Neural Networks
14 HoursPaddlePaddle
21 HoursAdvanced Machine Learning with R
21 HoursHardware-Accelerated Video Analytics
14 HoursAI Awareness for Telecom
14 HoursFrom Zero to AI
35 HoursAlgebra for Machine Learning
14 HoursAzure Machine Learning (AML)
21 HoursApplied Machine Learning
14 HoursAmazon Web Services (AWS) SageMaker
21 HoursAzure Machine Learning
14 HoursMachine Learning
21 HoursCore ML for iOS App Development
14 HoursDeepMind Lab
14 HoursMachine Learning Algorithms in Julia
21 HoursKubeflow
35 HoursKubeflow Fundamentals
28 HoursMathematica for Machine Learning
14 HoursMachine Learning – Data science
21 HoursMachine Learning and Big Data
7 HoursMachine Learning and AI with ML.NET
21 HoursMLflow
21 HoursIntroduction to Machine Learning
7 HoursMachine Learning on iOS
14 HoursMLOps: CI/CD for Machine Learning
35 HoursMLOps for Azure Machine Learning
14 HoursMachine Learning for Robotics
21 HoursOctave not only for programmers
21 HoursPractical Quantum Computing
10 HoursRecommender Systems with Python
14 HoursText Summarization with Python
14 HoursXGBoost for Gradient Boosting
14 HoursLast Updated:
Testimonials (23)
We had an overview about Machine Learning, Neural Networks, AI with practical examples.
Catalin - DB Global Technology SRL
Course - Machine Learning and Deep Learning
The trainer showed that he has a good understanding of the subject.
Marino - EQUS - The University of Queensland
Course - Machine Learning with Python – 2 Days
Keeping it short and simple. Creating intuition and visual models around the concepts (decision tree graph, linear equations, calculating y_pred manually to prove how the model works).
Nicolae - DB Global Technology
Course - Machine Learning
Interesting knowledge
Gabriel - MINDEF
Course - Machine Learning with Python – 4 Days
examples based on our data
Witold - P4 Sp. z o.o.
Course - Deep Learning for Telecom (with Python)
Fantastic training, one of the best I have ever attended! The moderator, Rafal, provided excellent answers to the issues raised and explained all the methods very thoroughly. JestI am very satisfied and will gladly take advantage of the training conducted by this trainer again.
Darek Paszkowski - Orange Szkolenia Sp. z o.o.
Machine Translated
The details and the presentation style.
Cristian Mititean - Accenture Industrial SS
Course - Azure Machine Learning (AML)
The structure from first principles, to case studies, to application.
Margaret Webb - Department of Jobs, Regions, and Precincts
Course - Introduction to Deep Learning
Working from first principles in a focused way, and moving to applying case studies within the same day
Maggie Webb - Department of Jobs, Regions, and Precincts
Course - Artificial Neural Networks, Machine Learning, Deep Thinking
the ML ecosystem not only MLFlow but Optuna, hyperops, docker , docker-compose
Guillaume GAUTIER - OLEA MEDICAL
Course - MLflow
Los ejemplos y la paciencia del instructor
José Emilio Sánchez García - Universidad Autónoma Indígena de México
Course - Natural Language Processing with TensorFlow
The way of transferring knowledge and the knowledge of the trainer.
Jakub Rękas - Bitcomp Sp. z o.o.
Course - Machine Learning on iOS
I enjoyed participating in the Kubeflow training, which was held remotely. This training allowed me to consolidate my knowledge for AWS services, K8s, all the devOps tools around Kubeflow which are the necessary bases to properly tackle the subject. I wanted to thank Malawski Marcin for his patience and professionalism for training and advice on best practices. Malawski approaches the subject from different angles, different deployment tools Ansible, EKS kubectl, Terraform. Now I am definitely convinced that I am going into the right field of application.
Guillaume Gautier - OLEA MEDICAL | Improved diagnosis for life™
Course - Kubeflow
That it was applying real company data. Trainer had a very good approach by making trainees participate and compete
Jimena Esquivel - Zakład Usługowy Hakoman Andrzej Cybulski
Course - Applied AI from Scratch in Python
The enthusiasm to the topic. The examples he made an he explained it very well. Sympatic. A little to detailed for beginners. For managers, it could be more abstract in fewer days. But it was designed to fit and we had a good alignment in advance.
Benedikt Chiandetti - HDI Deutschland Bancassurance Kundenservice GmbH
Course - Machine Learning Concepts for Entrepreneurs and Managers
Convolution filter
Francesco Ferrara
Course - Introduction to Machine Learning
Tomasz really know the information well and the course was well paced.
Raju Krishnamurthy - Google
Course - TensorFlow Extended (TFX)
Even with having to miss a day due to customer meetings, I feel I have a much clearer understanding of the processes and techniques used in Machine Learning and when I would use one approach over another. Our challenge now is to practice what we have learned and start to apply it to our problem domain
Richard Blewett - Rock Solid Knowledge Ltd
Course - Machine Learning – Data science
I was benefit from the passion to teach and focusing on making thing sensible.
Zaher Sharifi - GOSI
Course - Advanced Deep Learning
In-depth coverage of machine learning topics, particularly neural networks. Demystified a lot of the topic.
Sacha Nandlall
Course - Python for Advanced Machine Learning
Very updated approach or CPI (tensor flow, era, learn) to do machine learning.
Paul Lee
Course - TensorFlow for Image Recognition
I liked the opportunities to ask questions and get more in depth explanations of the theory.
Sharon Ruane
Course - Neural Networks Fundamentals using TensorFlow as Example
The trainer was so knowledgeable and included areas I was interested in.