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Nobleprog (uk) Limited courses

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  • City Of London

...loops for recommendation algorithms Logical regression, RankingSVM, Feature recognition (deep learning and automatic feature recognition for graphics)... Learn about: Data analysis, Artificial Intelligence... More


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...gives enterprises the freedom to integrate customized solutions into Nextcloud based on their specific needs. In this instructor-led, live training... More


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...Learning network – appropriate library, architecture definition Tuning network – initialization, activation functions, loss functions, optimization method... Learn about: Network Training... More


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...Learning as they step through the creation of a Deep Learning Agent. By the end of this training, participants will be able to: Understand the key concepts... More


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...projects After completing this course, delegates will: have a good understanding on deep neural networks(DNN), CNN and RNN understand TensorFlow’s structure... Learn about: Network Training... More


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...Basic operation of a CNN: convolutional layer, use of a kernel, Padding & stride, feature map generation, pooling layers. Extensions 1D, 2D and... Learn about: Network Training, Artificial Intelligence... More


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...Working with Neural Designer Using Neural Designer for descriptive, diagnostic, predictive and prescriptive analytics OpenNN architecture CPU parallelization... Learn about: Network Training... More


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...Bayes' theorem The naive Bayes algorithm The naive Bayes classification The Laplace estimator Using numeric features with naive Bayes 3.Understanding decision... Learn about: Network Training... More


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...DEEP LEARNING This will be taught in relation to the topics covered on Day 1 and Day 2 Logistic and Softmax Regression Sparse Autoencoders Vectorization... Learn about: Network Training... More


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...Naive Bayes Multinomial models Bayesian categorical data analysis Discriminant analysis Linear regression Logistic regression GLM EM Algorithm Mixed Models... More


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...The training is aimed at people who want to learn the basics of neural networks and their applications. The Basics Whether computers can think... Learn about: Network Training... More


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...File Structures Operations and Functions Working with Qubits Creating Your First Quantum Program with Q# Setting Up a Quantum Solution and Project in Visual... Learn about: Visual Studio... More


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...4)与稀疏特征学习的比较:注意数据的维数和稀疏影响。K-means通过寻找数据分布的”heavy-tailed"方向来找到输入数据的稀疏投影 5)在图像识别上的应用:更多的聚类中心往往是有帮助的。当然,前提是我们要有足够的训练样本 6)构建深度网络:尽可能地使用局部感受野。K-means是否成功,其瓶颈在于输入数据的维数,越低越好。如果无法手动的选择好的局部感受野,那么尝试去通过一个自动的依赖性测试来帮助从数据中挑选出一组低维的数据。... More


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...Neural Machine Translation model Convolutional Sequence to Sequence Learning Convolutional Encoder Model for Neural Machine Translation Standard LSTM-based... More


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...and Engineers whose company is venturing into AI space Business Analysts & Investors Introduction to Neural Networks Introduction to Applied Machine Learning... More


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...are beginners but also those who know the program and would like to systematize their knowledge and improve their skills. Knowledge of other programming languages is not required... More


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...serialization in Torch Coding exercise Loading a dataset in Torch MNIST CIFAR-10, CIFAR-100 Imagenet Machine Learning in Torch Deep Learning Manual feature... More


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...R is an open-source free programming language for statistical computing, data analysis, and graphics. R is used by a growing number of managers and... Learn about: Data Mining... More


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


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...Deep Learning for NLP allows a machine to learn simple to complex language processing. Among the tasks currently possible are language translation... More


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