Mathematical Engineering Deep Learning

Discover the concepts of deep learning used for natural language processing (NLP), with full-fledged examples of neural network models such as recurrent neural networks, long short-term memory networks, and sequence-2-sequence models.

In recent years, mathematical models, numerical methods and data analysis have been paid more attention. After the finite-element method, the meshless method is another effective tool for solving science and enginnering problems. Numerical methods, such as the finite-element method, boundary element method and meshless method, have played important roles in numerical simulations of complicated problems in the science, engineering and society fields. Various numerical methods are presented to solve problems in different fields, and their corresponding computational efficiency, accuracy and convergence are also studied. With the development of big data, numerical simulation based on data analysis or big data will be an important direction for science and engineering computation. Deep learning is another new and effective approach to analyzing the properties of new materials.

Covers Regression, Decision Trees, SVM, Neural Networks, CNN, Time Series Forecasting and more using both Python & R

Covers Regression, Decision Trees, SVM, Neural Networks, CNN, Time Series Forecasting and more using both Python & R

The Numpy, Scipy, Pandas, and Matplotlib stack: prep for deep learning, machine learning, and artificial intelligence

This textbook presents a concise, accessible and engaging first introduction to deep learning, offering a wide range of connectionist models which represent the current state-of-the-art. The text explores the most popular algorithms and architectures in a simple and intuitive style, explaining the mathematical derivations in a step-by-step manner.

Data science: Learn linear regression from scratch and build your own working program in Python for data analysis.

The Numpy, Scipy, Pandas, and Matplotlib stack: prep for deep learning, machine learning, and artificial intelligence