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MATLAB for Machine Learning: Practical examples of regression, clustering and neural networks
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MATLAB for Machine Learning: Practical examples of regression, clustering and neural networks
Get your first steps into machine learning with the help of this easy-to-follow guide
MATLAB for Machine Learning: Practical examples of regression, clustering and neural networks
Item #: 30028614

MATLAB for Machine Learning: Practical examples of regression, clustering and neural networks

Item #: 30028614

RON 379

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Get your first steps into machine learning with the help of this easy-to-follow guide
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What Stands Out

Comprehensive Examples
Offers practical, hands-on examples in regression, clustering, and neural networks, enhancing learning experiences by applying theory directly to real-world scenarios.
Focused on MATLAB
Utilizes MATLAB, a widely-used tool in academic and industry settings, providing a platform for effective machine learning model development and analysis.
Beginner-Friendly Approach
Designed for newcomers to machine learning, it breaks down complex concepts into manageable sections, ensuring a smooth learning curve for users with minimal prior knowledge.

Product Details

Explore regression, clustering and neural networks with MATLAB for Machine Learning. Find practical examples and boost your understanding. Shop now at Ubuy Romania.
  • Learn introductory concepts of machine learning using MATLAB
  • Explore regression techniques such as linear regression and correlations
  • Discover classification methods like Naive Bayes algorithm and Decision Trees in MATLAB
  • Understand clustering methods including hierarchical clustering in MATLAB
  • Master data fitting, pattern recognition, and clustering analysis using MATLAB Neural Network Toolbox
  • Learn feature selection and extraction for dimensionality reduction leading to improved performance
Item Weight1 lbs (450 grams)

Who Should Buy?

Suitable For
  • Aspiring Data Scientists

    Perfect for beginners looking to gain hands-on experience with basic machine learning techniques using MATLAB.

  • Engineering Students

    Ideal for students studying engineering or computer science who wish to understand practical applications of machine learning.

  • Professionals Upskilling

    Beneficial for professionals wanting to enhance their skill set in machine learning using a powerful mathematical tool.

Not Suitable For
  • Advanced Researchers

    Less suitable for researchers looking for cutting-edge algorithms or theoretical aspects of machine learning.

  • Non-programmers

    Not ideal for individuals without programming knowledge, as MATLAB requires technical proficiency for effective usage.

  • Budget-conscious Learners

    Not recommended for those seeking free resources, as MATLAB is a paid software with associated licensing costs.

Product Description

MATLAB for Machine Learning: Practical examples of regression, clustering and neural networks

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Customer Questions & Answers

  • Question: What is the main focus of MATLAB for Machine Learning?

    Answer: The main focus of MATLAB for Machine Learning is to provide practical examples of key machine learning techniques, including regression, clustering, and neural networks. MATLAB offers a user-friendly environment that makes it easy to implement these complex algorithms without extensive programming knowledge. Users can explore various data sets, understand the underlying mathematical concepts, and visualize results effectively, enhancing their learning experience. For instance, a beginner can follow a guided example on regression to predict outcomes based on input variables, building a strong foundation in machine learning principles.
  • Question: How does regression work in the context of MATLAB for Machine Learning?

    Answer: Regression in MATLAB for Machine Learning signifies a method used to predict a continuous output variable based on one or more input features. The book provides step-by-step guidelines that cover the creation of models, evaluation metrics, and visualization of the regression lines. For example, users can use regression to predict house prices based on size and location, employing MATLAB's built-in functions for quick implementation and interpretation of results.
  • Question: What are the applications of clustering demonstrated in the book?

    Answer: The book illustrates various clustering techniques that group similar data points together without prior knowledge of labels. Applications include market segmentation, image segmentation, and anomaly detection. For instance, a marketer can use clustering to identify distinct customer segments based on purchasing behaviors, allowing for tailored marketing strategies. Using MATLAB's visualization tools, users can easily interpret the clustered data and make informed decisions.
  • Question: Can I learn about neural networks using MATLAB?

    Answer: Yes, MATLAB for Machine Learning covers neural networks extensively, guiding users through the process of designing, training, and validating these models. The book explains various neural network architectures suitable for different tasks, such as classification and regression problems. For example, a researcher interested in image classification can implement a convolutional neural network (CNN) in MATLAB, benefiting from the platform’s interactive components for model performance assessment.
  • Question: Is MATLAB suitable for beginners in machine learning?

    Answer: Yes, MATLAB is highly suitable for beginners due to its intuitive interface and extensive documentation. The book starts with fundamental concepts of machine learning before progressing to more advanced topics, ensuring that readers build a solid understanding. Beginners can benefit from interactive examples that allow hands-on experimentation, fostering a deeper understanding of how algorithms function and their real-world applications.
  • Question: Does the book provide real-world examples for practice?

    Answer: Absolutely! The book is packed with real-world examples that illustrate how to apply various machine learning techniques using MATLAB. These examples encompass different industries such as healthcare, finance, and marketing, making the content relevant for diverse fields. Readers can try their hands on practical use cases such as predicting patient outcomes based on historical data, ultimately bridging the gap between theory and practice.
  • Question: How does one install MATLAB to access the book's content?

    Answer: To access the book's content, it's crucial first to install a compatible version of MATLAB. Installation typically involves downloading the software from the official MathWorks website and following the provided setup guidelines. Once installed, users can explore the examples presented in the book by running them directly within the MATLAB environment, facilitating a seamless learning experience.
  • Question: What prerequisites are needed to understand MATLAB for Machine Learning?

    Answer: A basic understanding of programming concepts and familiarity with mathematical principles such as linear algebra and statistics will significantly enhance the learning experience with MATLAB for Machine Learning. However, the book starts from foundational theories, enabling readers with varying levels of expertise to follow along. Practical scenarios ensure that users can apply theoretical knowledge to real-world problems, regardless of their prior experience.
  • Question: Where can I buy MATLAB for Machine Learning in Romania?

    Answer: You can buy MATLAB for Machine Learning: Practical examples of regression, clustering, and neural networks from Ubuy in Romania. Ubuy offers a convenient platform to purchase the book along with MATLAB software, allowing users to easily access the necessary resources for their machine learning studies.

Intelligence & Semantics Editorial Review

This book provides a practical introduction to machine learning using MATLAB. It covers regression, clustering, and neural networks with step-by-step examples. While it lacks in-depth mathematical explanations, it offers a clear understanding of the general analysis process in machine learning.

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Pros

  • Practical examples for regression, clustering, and neural networks
  • Clear step-by-step instructions using MATLAB
  • Provides a general understanding of machine learning analysis

Cons

  • Lacks detailed mathematical explanations

Product Price History

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RON 379

Order now and get it around Wednesday, June 24

QTY:

Secured transactionsecured transaction

Ubuy works hard to protect your security and privacy. Our advanced payment security system ensures confidentiality by encrypting your information during transmission using AES (Advanced Encryption Standards) and SSL (Secure Socket Layer) protocols. Your payment details are 100% secure as we do not share your payment details with third party sellers.

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Features & Benefits

  • Learn introductory concepts of machine learning
  • Discover different ways to transform data using SAS XPORT, import and export tools
  • Explore different types of regression techniques
  • Implement Naive Bayes algorithm and Decision Trees in the Matlab environment
  • Perform data fitting, pattern recognition, and clustering analysis
  • Learn feature selection and extraction for dimensionality reduction