-
All
-
Online
-
Filters
Nobleprog Limited courses
- Course
- City Of London
...Introduction Reinforcement Learning Basics Basic Reinforcement Learning Techniques Introduction to BURLAP Convergence of Value and Policy Iteration Reward...
- Course
- City Of London
...of a neural network: L1 / L2 regularization, Batch Normalization Optimization and convergence algorithms Standard ML / DL Tools A simple presentation with advantages... Learn about: Network Training...
- Course
- City Of London
...an introduction to Deep Learning as well as to its various fields of specialization and therefore to the main existing network architectures today... Learn about: Artificial Intelligence, Network Training...
- Course
- City Of London
...Compiling with QT Creator Integrating, testing and debugging your application The future of neural networks and OpenNN... Learn about: Network Training...
- Course
- City Of London
...Precision and recall The F-measure Visualizing performance tradeoffs ROC curves Estimating future performance The holdout method Cross-validation Bootstrap sampling... Learn about: Network Training...
- Course
- City Of London
...DAY 1 - ARTIFICIAL NEURAL NETWORKS Introduction and ANN Structure. Biological neurons and artificial neurons. Model of an ANN. Activation functions used in... Learn about: Network Training...
- Course
- City Of London
...Additive Models Classification KNN Bayesian Graphical Models Factor Analysis (FA) Principal Component Analysis (PCA) Independent Component Analysis (ICA)...
- Course
- City Of London
...Imperative and declarative approach to solving problems Purpose Bedan on artificial intelligence The definition of artificial intelligence. Turing... Learn about: Network Training...
- Course
- City Of London
...Language and Compiler Q# Standard Library Local Quantum Machine Simulator Quantum Trace Simulator Visual Studio Extension Installing and Configuring Microsoft's... Learn about: Visual Studio...
- Course
- City Of London
...2.2稀疏滤波Sparse Filtering 1）核心思想就是避免对数据分布的显式建模，而是优化特征分布的稀疏性从而得到好的特征表达 2）非监督特征学习：学习一个模型，这个模型描述的就是数据真实分布的一种近似。包括denoisingautoencoders，restricted Boltzmann machines...
- Course
- City Of London
...model Overview of training approaches About GPUs and CPUs Fast beam search generation Installation and setup Evaluating pre-trained models Preprocessing...
- Course
- City Of London
...and Engineers whose company is venturing into AI space Business Analysts & Investors Introduction to Neural Networks Introduction to Applied Machine Learning...
- Course
- City Of London
...Complex numbers Plotting complex numbers, Statistics and data processing GUI Development...
- Course
- City Of London
...along the way to check understanding Introduction to Torch Like NumPy but with CPU and GPU implementation Torch's usage in machine learning...
- Course
- City Of London
...Cross-validation and Resampling Cross-validation approaches Bootstrap Exercises Unsupervised Learning K-means clustering Examples Challenges of unsupervised... Learn about: Data Mining...
- Course
- City Of London
...Reconstructing the Original Input Data from a Corrupted (Noisy) Version Feature Selection and Extraction Stacked Denoising Auto-encoders Analyzing Visual... Learn about: Financial Training...
- Course
- City Of London
...for Deep Learning for NLP. In this instructor-led, live training, participants will learn to use Python libraries for NLP (Natural Language Processing)...
- Course
- City Of London
...part discussion, exercises and heavy hands-on practice Note To request a customized training for this course, please contact us to arrange. Introduction...
- Course
- City Of London
...used in the field of pattern matching as it applies to Machine Vision. Introduction Computer Vision Machine Vision Pattern Matching vs Pattern Recognition...
- Course
- City Of London
...the course The basic principles of image analysis, video analysis and the Marvin Framework are first introduced. Students are given project-based tasks...