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- 7.000.000 titres dans notre catalogue
- Payer en toute sécurité
- Toujours un magasin près de chez vous
Practical MATLAB Deep Learning
A Project-Based Approach
Michael Paluszek, Stephanie Thomas
Livre broché | Anglais
39,45 €
+ 78 points
Format
Description
Harness the power of MATLAB for deep-learning challenges. This book provides an introduction to deep learning and using MATLAB's deep-learning toolboxes. You'll see how these toolboxes provide the complete set of functions needed to implement all aspects of deep learning.
Along the way, you'll learn to model complex systems, including the stock market, natural language, and angles-only orbit determination. You'll cover dynamics and control, and integrate deep-learning algorithms and approaches using MATLAB. You'll also apply deep learning to aircraft navigation using images.
Finally, you'll carry out classification of ballet pirouettes using an inertial measurement unit to experiment with MATLAB's hardware capabilities. What You Will Learn
Engineers, data scientists, and students wanting a book rich in examples on deep learning using MATLAB.
Along the way, you'll learn to model complex systems, including the stock market, natural language, and angles-only orbit determination. You'll cover dynamics and control, and integrate deep-learning algorithms and approaches using MATLAB. You'll also apply deep learning to aircraft navigation using images.
Finally, you'll carry out classification of ballet pirouettes using an inertial measurement unit to experiment with MATLAB's hardware capabilities. What You Will Learn
- Explore deep learning using MATLAB and compare it to algorithms
- Write a deep learning function in MATLAB and train it with examples
- Use MATLAB toolboxes related to deep learning
- Implement tokamak disruption prediction
Engineers, data scientists, and students wanting a book rich in examples on deep learning using MATLAB.
Spécifications
Parties prenantes
- Auteur(s) :
- Editeur:
Contenu
- Nombre de pages :
- 252
- Langue:
- Anglais
Caractéristiques
- EAN:
- 9781484251232
- Date de parution :
- 08-02-20
- Format:
- Livre broché
- Format numérique:
- Trade paperback (VS)
- Dimensions :
- 178 mm x 254 mm
- Poids :
- 471 g
