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Showing results for "data analytics curriculum"

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AI Rookies Labs Beginning NLP with Orange

Visual, No-Code Text Analysis

2025

EN

AI Rookies Labs: Beginning NLP with Orange is a hands-on, visual lab workbook that introduces students to natural language processing (NLP) using the no-code Orange data mining platform. Designed for high school, college, and independent learners, this book teaches core concepts such as text preprocessing, sentiment analysis, topic modeling, and text classification-without requiring any programming experience. Each lab guides readers through step-by-step workflows using drag-and-drop widge...

PHP1,383.89

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2013

EN

This is a tutorial-driven and practical, but well-grounded book showcasing good Machine Learning practices. There will be an emphasis on using existing technologies instead of showing how to write your own implementations of algorithms. This book is a scenario-based, example-driven tutorial. By the end of the book you will have learnt critical aspects of Machine Learning Python projects and experienced the power of ML-based systems by actually working on them.This book primarily targets Py...

Deep Learning for Computer Vision

Expert techniques to train advanced neural networks using TensorFlow and Keras

2018

EN

Learn how to model and train advanced neural networks to implement a variety of Computer Vision tasksKey Features\[\*\] Train different kinds of deep learning model from scratch to solve specific problems in Computer Vision\[\*\] Combine the power of Python, Keras, and TensorFlow to build deep learning models for object detection, image classification, similarity learning, image captioning, and more\[\*\] Includes tips on optimizing and improvi...

Deep Learning Cookbook

Practical Recipes to Get Started Quickly

2018

EN

Deep learning doesn’t have to be intimidating. Until recently, this machine-learning method required years of study, but with frameworks such as Keras and Tensorflow, software engineers without a background in machine learning can quickly enter the field. With the recipes in this cookbook, you’ll learn how to solve deep-learning problems for classifying and generating text, images, and music.Each chapter consists of several recipes needed to complete a single project, such as train...

PHP2,140.09

Advanced Analytics with R and Tableau

Advanced analytics using data classification, unsupervised learning and data visualization

2017

EN

Leverage the power of advanced analytics and predictive modeling in Tableau using the statistical powers of RKey FeaturesA comprehensive guide that will bring out the creativity in you to visualize the results of complex calculations using Tableau and RCombine Tableau analytics and visualization with the power of R using this step-by-step guideWondering how R can be used with Tableau? This book is your one-stop solution.Book Descr...

Building Machine Learning Systems with Python

Explore machine learning and deep learning techniques for building intelligent systems using scikit-learn and TensorFlow

2018

EN

Build intelligent end-to-end machine learning systems with PythonKey FeaturesUse scikit-learn and TensorFlow to train your machine learning modelsImplement popular supervised and unsupervised machine learning algorithms in PythonDiscover best practices for building production-grade machine learning systems from scratchBook DescriptionMachine learning enables systems to make predictions based on historical data. Python is one ...

Hands-On Natural Language Processing with Python

A practical guide to applying deep learning architectures to your NLP applications

2018

EN

Foster your NLP applications with the help of deep learning, NLTK, and TensorFlowKey FeaturesWeave neural networks into linguistic applications across various platformsPerform NLP tasks and train its models using NLTK and TensorFlowBoost your NLP models with strong deep learning architectures such as CNNs and RNNsBook DescriptionNatural language processing (NLP) has found its application in various domains, such as web search...

Machine Learning for OpenCV 4

Intelligent algorithms for building image processing apps using OpenCV 4, Python, and scikit-learn

2019

EN

A practical guide to understanding the core machine learning and deep learning algorithms, and implementing them to create intelligent image processing systems using OpenCV 4Key FeaturesGain insights into machine learning algorithms, and implement them using OpenCV 4 and scikit-learnGet up to speed with Intel OpenVINO and its integration with OpenCV 4Implement high-performance machine learning models with helpful tips and best practices

Python Machine Learning By Example

Implement machine learning algorithms and techniques to build intelligent systems


2019

EN

Grasp machine learning concepts, techniques, and algorithms with the help of real-world examples using Python libraries such as TensorFlow and scikit-learnKey FeaturesExploit the power of Python to explore the world of data mining and data analyticsDiscover machine learning algorithms to solve complex challenges faced by data scientists todayUse Python libraries such as TensorFlow and Keras to create smart cognitive actions for your projects

2023

EN

Academic English for Computer Science aims to provide a tool for the effective study of computational science and technology. It addresses international students who use English as a second language. It can be used as a foundation course in undergraduate programs of computer science, computer engineering, and information technology.The material of this course draws content from core areas of computer science, aspiring to create an initial induction in the field. Fu...

PHP1,929.47

2014

EN

This short booklet will introduce you to the Star programming language, what is novel about it and why you should know more.Star is a modern functional first programming language that has a rich set of features. It is readable, safe and extensible. It supports multiple paradigms including actor based programming, query based programming, and concurrent programming.The booklet highlights some of the key features of the language and gives extended examples including showing h...

Free

Distributed Systems

Concurrency and Consistency

2017

EN

Accessible

Distributed Systems: Concurrency and Consistency explores the gray area of distributed systems and draws a map of weak consistency criteria, identifying several families and demonstrating how these may be implemented into a programming language. Unlike their sequential counterparts, distributed systems are much more difficult to design, and are therefore prone to problems. On a large scale, usability reminiscent of sequential consistency, which would provide the same global view to all use...

PHP5,363.09