Nobleprog Limited courses

...behind Deep Reinforcement Learning and be able to distinguish it from Machine Learning Apply advanced Reinforcement Learning algorithms to solve real-world...

...presentation and examples Data Augmentation: how to balance a dataset Generalization of the results of a network of neurons. Initialization and regularization... Learn about: Network Training...

...Use of an attention model. - Application to a common classification case (text or image) - CNNs for generation: super-resolution, pixel-to-pixel segmentation... Learn about: Artificial Intelligence, Network Training...

...of neural networks and use OpenNN to implement a sample application. Audience Software developers and programmers wishing to create Deep Learning applications... Learn about: Network Training...

...tasks. Neural Networks are commonly used in Machine Learning (ML) applications, which are themselves one implementation of AI. Deep Learning is a subset of... Learn about: Network Training...

...2 MACHINE LEARNING The PAC Learning Framework Guarantees for finite hypothesis set – consistent case Guarantees for finite hypothesis set – inconsistent... Learn about: Network Training...

...on the practical aspects of data/model preparation, execution, post hoc analysis and visualization. The purpose is to give practical applications to Machine...

...a network Neurons Layers Scales Input and output data Range 0 to 1 Normalization Learning Neural Networks Backward Propagation Steps propagation Network... Learn about: Network Training...

...In this instructor-led, live training, participants will learn the fundamentals of quantum computing and Q# as they step through the development of simple quantum programs... Learn about: Visual Studio...

...6）学习曲线：什么时候增加训练数据才是有效的 过拟合的高方差: 增加m使得J(train)和J(cv)之间gap减小，有助于性能提高； 增加训练数据的个数对于过拟合是有用的，对于欠拟合是徒劳 1.7 机器学习系统设计 1）决定基本策略：收集大量数据；提取复杂特征；建立精确的特征库； 2）Error分析...

...participants will have the knowledge and practice needed to implement a live Fairseq based machine translation solution. Audience Localization specialists...

...Learning Technical Overview R v/s Python Caffe v/s Tensor Flow Various Machine Learning Libraries Industry Case Studies...

...but it will greatly facilitate the learners' acquisition of knowledge. The course will show you how to use the program in many practical examples. Introduction...

...demonstrating and practicing the concepts learned. By the end of the course, participants will have a thorough understanding of Torch's underlying features...

...Machine learning Iteration and evaluation Bias-Variance trade-off Regression Linear regression Generalizations and Nonlinearity Exercises Classification... Learn about: Data Mining...

...Extraction Building Highly Accurate Predictive Models Improving Machine Learning Results Ensemble Methods Summary and Conclusion... Learn about: Financial Training...

...Creating a simple Deep Learning application in TensorFlow to add captions to a collection of pictures Troubleshooting A word on other (specialized)...

...Install and configure RapidMiner Prepare and visualize data with RapidMiner Validate machine learning models Mashup data and create predictive models Operationalize...

...used in the field of pattern matching as it applies to Machine Vision. Introduction Computer Vision Machine Vision Pattern Matching vs Pattern Recognition...

...Introduction to Marvin Downloading and installing Marvin Setting up an Eclipse development environment The three layers of the Marvin architecture Framework...