Packt – Speech Recognition A-Z With Hands-on

Packt – Speech Recognition A-Z With Hands-on-iLLiTERATE
English | Size: 3.04 GB
Category: Tutorial


Are you intrigued by how speech recognition is driving the growth of the AI market? This course is a reliable guide if you’re looking to pursue a career as a speech recognition professional and understand industry best practices. You’ll learn the science of applying machine learning algorithms to process large amounts of speech data. As you progress, the course will get you up to speed with automated speech recognition. Later, you’ll delve into speech translation, understanding how to work through speech-to-speech translation. Toward the concluding sections, you’ll focus on voice conversion, exploring everything from Phonetic SID System to speaker identification. Throughout the course, you’ll encounter practice questions to help you reinforce your knowledge. [Read more…]

Packt – Computer Vision: Face Recognition Quick Starter in Python

Packt – Computer Vision Face Recognition Quick Starter in Python-RiDWARE
English | Size: 1.92 GB
Category: Tutorial


Face detection and face recognition are the most popular aspects in computer vision. They are widely used by governments and organizations for surveillance and policing. Moreover, they also have applications in our day-to-day life such as face unlocking mobile phones. [Read more…]

Packt – Computer Vision Face Recognition Quick Starter in Python [Video]

Packt – Computer Vision_ Face Recognition Quick Starter in Python [Video]
English | Size: 1.93 GB
Category: Tutorial


Build Python deep learning-based face detection, recognition, emotion, gender and age classification systems [Read more…]

PluralSight – Creating Named Entity Recognition Systems with Python

PluralSight – Creating Named Entity Recognition Systems with Python-BOOKWARE-KNiSO
English | Size: 166.79 MB
Category: Tutorial


Release Notes: In this course, Creating Named Entity Recognition Systems with Python, you’ll look at how data professionals and software developers make use of the Python language. First, you’ll explore the unique ability of such systems to perform information retrieval by identifying specific classes of entities in texts Next, you’ll learn how to install prerequisite tools and how to create in a step-by-step manner all the specific components of performant NER systems Finally, you’ll be able to create Named Entity Recognition (NER) systems by leveraging the language s powerful set of open-source NLP libraries. When you re finished with this course, you ll have the skills and knowledge of creating named entity recognition systems with Python [Read more…]

Linkedin Learning – Deep Learning Image Recognition

Linkedin Learning – Deep Learning Image Recognition-ZH
English | Size: 307.54 MB
Category: Tutorial

Thanks to deep learning, image recognition systems have improved and are now used for everything from searching photo libraries to generating text-based descriptions of photographs. In this course, learn how to build a deep neural network that can recognize objects in photographs. Find out how to adjust state-of-the-art deep neural networks to recognize new objects, without the need to retrain the network. Explore cloud-based image recognition APIs that you can use as an alternative to building your own systems. Learn the steps involved to start building and deploying your own image recognition system [Read more…]

Technics Publications – Data Science and Machine Learning Series Facial Detection and Recognition using OpenCV

Technics Publications – Data Science and Machine Learning Series: Facial Detection and Recognition using OpenCV (BONUS: Create your own Snapchat Filter!)-ZH
English | Size: 477.00 MB
Category: Tutorial

Apply facial recognition using OpenCV in this course within the Data Science and Machine Learning Series. Follow along with machine learning expert Advait Jayant through a combination of lecture and hands-on to practice facial recognition software, including one project where you will build your own Snapchat Filter! [Read more…]