This Diploma in Deep Learning for Data Mining emerges as a an essential component of the artificial intelligence ecosystem, given its current relevance. By merging the the power of Python with specialised libraries such as Keras and TensorFlow, this training programme is in response to the growing demand for professionals capable of designing, implementing and optimising neural networks. Based on the fundamental concepts of deep learning and moving on to the practical application in data mining, the programme offers a a comprehensive overview of how deep learning drives the interpretation and extraction of patterns in large datasets, making it easier to informed decision-making.
Cross-cutting
AI Academy
25 hours
Deep Learning in Data Mining
AI Academy
25 hours
Introduction
Objectives
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Understanding the fundamentals of deep learning and his implementation in Python.
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Distinguishing between deep and shallow neural networks, by understanding their applications.
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Master the design and application of perceptrons from a single layer and multiple layers.
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Identify and apply learning strategies in multilayer networks.
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Exploring the KDD process and his in relation to data mining.
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Apply data mining models and techniques in areas such as copywriting and marketing.
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Implement forward propagation algorithms for train deep neural networks.
Table of Contents
TEACHING UNIT 1. DEEP LEARNING WITH PYTHON, KERAS AND TENSORFLOW
Deep learning
Deep Learning Environment with Python
Machine learning and deep learning
TEACHING UNIT 2. NEURAL SYSTEMS
Neural networks
Deep networks and shallow networks
TEACHING UNIT 3. SINGLE-LAYER NETWORKS
Single-layer and multi-layer perceptrons
Example of a perceptron
TEACHING UNIT 4. MULTILAYER NETWORKS
Types of deep networks
TEACHING UNIT 5. LEARNING STRATEGIES
Training a neural network
Computer graphics
Implementation of a deep neural network
The direct propagation algorithm
Multilayer deep neural networks
TEACHING UNIT 6. DATA MINING AND MACHINE LEARNING
An Introduction to Data Mining and Machine Learning
KDD Process
Data Mining Models and Techniques
Areas of application
Text Mining and Web Mining
Data mining and marketing
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