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Advanced Learning Algorithms

Neural Networks This week, you’ll learn about neural networks and how to use them for classification tasks. You’ll use the TensorFlow framework to build a neural network with just a few lines of code. Then,…

Advanced Machine Learning Algorithms

Getting Familiar with Regularisation In the fast-evolving field of machine learning, overfitting and underfitting are persistent challenges that can hinder the performance of models. The Regularization module delves deep into the techniques that address these…

Basic Modeling for Discrete Optimization

MiniZinc introduction In this first module, you will learn the basics of MiniZinc, a high-level modeling language for discrete optimization problems. Combining the simplicity of MiniZinc with the power of open-source industrial solving technologies, you…

Approximation Algorithms Part I

Vertex cover and Linear Programming We introduce the course topic by a typical example of a basic problem, called Vertex Cover, for which we will design and analyze a state-of-the-art approximation algorithm using two basic…

Approximation Algorithms Part II

Linear Programming Duality This module does not study any specific combinatorial optimization problem. Instead, it introduces a central feature of linear programming, duality. Steiner Forest and Primal-Dual Approximation Algorithms This module uses linear programming duality…

Analysis of Algorithms

Analysis of Algorithms We begin by considering historical context and motivation for the scientific study of algorithm performance. Then we consider a classic example that illustrates the key ingredients of the process: the analysis of…

Análisis de texto en archivos con Azure cognitive search

Análisis de texto en archivos con Azure cognitive search Al final de este proyecto, tú entenderás y aplicarás algunos servicios de Azure para poder analizar documentos de texto en un motor de búsqueda para que…

Graph Search, Shortest Paths, and Data Structures

Algorithms, Part II

Introduction Welcome to Algorithms, Part II. Undirected Graphs We define an undirected graph API and consider the adjacency-matrix and adjacency-lists representations. We introduce two classic algorithms for searching a graph—depth-first search and breadth-first search. We…

Algorithms, Part I

Course Introduction Welcome to Algorithms, Part I. Union−Find We illustrate our basic approach to developing and analyzing algorithms by considering the dynamic connectivity problem. We introduce the union−find data type and consider several implementations (quick…

Divide and Conquer, Sorting and Searching, and Randomized Algorithms

Week 1 Introduction; «big-oh» notation and asymptotic analysis. Week 2 Divide-and-conquer basics; the master method for analyzing divide and conquer algorithms. Week 3 The QuickSort algorithm and its analysis; probability review. Week 4 Linear-time selection;…

Algorithms for Searching, Sorting, and Indexing

Basics of Algorithms Through Searching and Sorting In this module the student will learn the very basics of algorithms through three examples: insertion sort (sort an array in ascending/descending order); binary search: search whether an…

Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming

Week 1 Two motivating applications; selected review; introduction to greedy algorithms; a scheduling application; Prim’s MST algorithm. Week 2 Kruskal’s MST algorithm and applications to clustering; advanced union-find (optional). Week 3 Huffman codes; introduction to…

Algoritmos de negociación basados en machine learning​

Mercados Financieros Bienvenido al primer módulo del curso algoritmos de negociación basados en machine learning. En este módulo comprenderemos el funcionamiento de los mercados financieros, identificaremos cuáles son las principales decisiones de inversión, entenderemos cómo…

Advanced Modeling for Discrete Optimization

Debugging and Improving Models Similar to computer programs, models can have bugs. In this module, you will see the symptoms (unsatisfiability, too many solutions, too few solutions) of different bugs, and learn methods to discover…