Yerdaulet Z.

More about my key skills: - Neural Networks components: Dropout, Batch Normalization, Layer Normalization. - Neural Network Architectures: CNN, RNN, GRU, LSTM, AlexNet, ResNet, VGG, WGAN-GP. - Loss function: Connectionist Temporal Classification. - Machine Learning Algorithms: Linear regression, Logistic Regression, KNN, K-means, K-means ++, Decision Tree Regressor & Classifier, Random Forest Classifier, AdaBoost Classifier, Gradient Boost Regressor & Classifier. - Optimization algorithms: Gradient Descent, Mini-Batch Stochastic Gradient Descent, Stochastic Gradient Descent with Momentum, AdaGrad, RMSProp, Adam. - Regularization: L1, L2. - Understanding parameter optimization using the chain rule