Python and R course by a Machine Learning and Actuarial Researcher

Hello, I am an experienced machine learning teacher with 5 years of expertise in teaching this discipline at all levels. My expertise using Python and R allows me to teach different machine learning algorithms such as neural networks, decision trees and clustering algorithms. I am also experienced in using popular Python and R libraries such as TensorFlow, Keras, Scikit-learn and ggplot2. In addition to my machine learning skills, I am able to help students read and understand research papers for their presentations, as well as work on projects in Python and R. My commitment to machine learning is passionate and I enjoy sharing my knowledge with my students. If you are interested in my services as a machine learning teacher for all levels, do not hesitate to contact me. In addition to my machine learning skills, I am also able to help you with mathematics, statistics and dissertation writing. I am available to teach the following subjects: 1.Python or R 2. Data exploration 3.Machine learning 3.1. Intro ML 3.2. Linear Model -> Linear Models for Regression and Classification 3.3. kernel -> Kernelization 3.4. Model selection 3.5. model set, -> Bagging / RandomForest, Boosting (XGBoost, LightGBM,...) , Stacking 3.6. Data preprocessing -> Data pre-processing -> Pipelines: choose the right preprocessing steps and models in your pipeline -> Cross validation 3.7. Neural Networks -> Neural architectures -> Training neural nets: Forward pass: Tensor operations and Backward pass: Backpropagation -> Neural network design: Activation functions, weight initialization and Optimizers -> Neural networks in practice: Model selection, Early stopping, Memorization capacity and information bottleneck, L1/L2 regularization, Dropout, Batch normalization 3.8. Convolutional Neural Networks -> Convolved Image -> Convolutional neural networks ->Data increase -> Model interpretation -> Using pre-trained networks (transfer learning) 3.9. Neural Networks for text -> Bag of word representations, Word embeddings, Word2Vec, FastText, GloVe