This instructor-led, live training in 上海 (online or onsite) is aimed at beginner-level participants who wish to learn essential concepts in probability, statistics, programming, and machine learning, and apply these to AI development.
By the end of this training, participants will be able to:
Understand basic concepts in probability and statistics, and apply them to real-world scenarios.
Write and understand procedural, functional, and object-oriented programming code.
Implement machine learning techniques such as classification, clustering, and neural networks.
Develop AI solutions using rules engines and expert systems for problem-solving.
This instructor-led, live training in 上海 (online or onsite) is aimed at intermediate-level data scientists and statisticians who wish to prepare data, build models, and apply machine learning techniques effectively in their professional domains.
By the end of this training, participants will be able to:
Understand and implement various Machine Learning algorithms.
Prepare data and models for machine learning applications.
Conduct post hoc analyses and visualize results effectively.
Apply machine learning techniques to real-world, sector-specific scenarios.
This instructor-led, live training in 上海 (online or onsite) provides an introduction into the field of pattern recognition and machine learning. It touches on practical applications in statistics, computer science, signal processing, computer vision, data mining, and bioinformatics.
By the end of this training, participants will be able to:
Apply core statistical methods to pattern recognition.
Use key models like neural networks and kernel methods for data analysis.
Implement advanced techniques for complex problem-solving.
Improve prediction accuracy by combining different models.
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
课程 - Deep Learning with TensorFlow 2.0
Tomasz really know the information well and the course was well paced.
Raju Krishnamurthy - Google
课程 - TensorFlow Extended (TFX)
Organization, adhering to the proposed agenda, the trainer's vast knowledge in this subject
Ali Kattan - TWPI
课程 - Natural Language Processing with TensorFlow
The trainer was a professional in the subject field and related theory with application excellently
Fahad Malalla - Tatweer Petroleum
课程 - Applied AI from Scratch in Python
In-depth coverage of machine learning topics, particularly neural networks. Demystified a lot of the topic.
Sacha Nandlall
课程 - Python for Advanced Machine Learning
Very updated approach or CPI (tensor flow, era, learn) to do machine learning.
Paul Lee
课程 - TensorFlow for Image Recognition
I liked the new insights in deep machine learning.
Josip Arneric
课程 - Neural Network in R
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
课程 - Machine Learning and Deep Learning
The global overview of deep learning.
Bruno Charbonnier
课程 - Advanced Deep Learning
The topic is very interesting.
Wojciech Baranowski
课程 - Introduction to Deep Learning
Ann created a great environment to ask questions and learn. We had a lot of fun and also learned a lot at the same time.
Gudrun Bickelq
课程 - Introduction to the use of neural networks
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
课程 - Artificial Neural Networks, Machine Learning, Deep Thinking
