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Discover the Best Private Computers & electronics Classes in Staines‑Upon‑Thames

For over a decade, our private Computers & electronics tutors have been helping learners improve and realise their ambitions. With one-to-one lessons at your home or in Staines‑Upon‑Thames, you’ll enjoy high-quality, personalised teaching that’s tailored to your goals, availability, and learning style.

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1 computers & electronics teacher in Staines‑Upon‑Thames

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1 computers & electronics teacher in Staines‑Upon‑Thames

Jhosimar - Peru£23
£23Private or group classes of Machine Learning and Deep Learning
Trusted teacher: Master in Computer Science from the State University of Campinas (Brazil) and university professor in Peru. He has participated in the most important Artificial Intelligence conferences including ACL, NeurIPS, ICML, ICLR, KDD, ICCV and CVPR, summer schools such as Machine Learning (MLSS), Deep Learning (DLRL) and Probabilistic ML (ProbAI). He has also participated in various programming contests and has experience preparing interviews for applications to companies such as Google, Meta, Microsoft, among others. He has extensive experience in the areas of Machine Learning and Deep Learning applied mainly to computer vision and natural language processing. He has experience in teaching, providing illustrative explanations for a better understanding of both the theoretical and practical parts. Some examples of presentations given: - He has also advised students from different countries in their graduation and master's theses, providing them with a theoretical and practical base with examples that they can then use to continue their development. Some of the things I can help you with: - Machine Learning: Linear regression, logistic regression, regularization, LDA, QDA, SVMs, decision trees, random forest, boosting, PCA, clustering (K-means, DBSCAN, hierarchical, GMM), neural networks, model selection, metrics evaluation, MLE, Bayesian learning, data preprocessing, etc. - Deep Learning: Multilayer Perceptron (MLP), backpropagation, activation functions, multiclass classification, optimizers (SGD, Adam, RMSProp, etc.), CNNs, architectures (ResNet, DenseNet, EfficientNet, Siamese, etc.), RNNs, LSTMs, Seq2seq, Attention, Transformers (BERT, GPT, ViT, etc.), autoencoders, generative models (VAE, GAN, Diffusion, etc.), etc. - Languages: Python, C++ - Libraries and frameworks: PyTorch, Tensorflow, Keras, Huggingface, numpy, pandas, scikit-learn, sympy, etc.
Computer programming · Python
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