Natural Language Processing Courses

104 Courses

Udemy

NLP. Procesamiento del lenguaje natural con NLP y Python

NLP: Procesamiento del Lenguaje Natural con NLP y Python | Udemy Aprende a usar Machine Learning, Scikit-learn, Spacy y NLTK para procesar textos de ficheros y documentos con NLP. Este curso te ofrece habilidades prácticas y conocimientos fundamentales para dominar el Procesamiento del Lenguaje Natural con Python. University: Udemy Python Cour.

Pluralsight

Introduction to NLP for Data Practitioners

Introduction to NLP for Data Practitioners Have you ever wondered how virtual assistants understand voice commands or how social media deciphers sentiments? This course will teach you how to extract insights from text data by executing an end-to-end NLP pipeline. Besides deriving meaningful insights from data such a.

Udacity

AWS Machine Learning Engineer Nanodegree

AWS Machine Learning Engineer Nanodegree AWS Machine Learning Engineer Nanodegree The AWS Machine Learning Engineer (MLE) Nanodegree program aims to empower software developers and data scientists with essential data science and machine learning skills. This program emphasizes the construction and deployment of machine learning.

Udacity

Natural Language Processing

Natural Language Processing Course | Udacity Master the skills to get computers to understand, process, and manipulate human language with Udacity's comprehensive Natural Language Processing course. Build models on real data, and gain hands-on experience with key techniques like sentiment analysis and machine translation. U.

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Introduction to NLP

As a technical specialist, an NLP engineer is responsible for empowering businesses with natural language processing. He implements knowledge-intensive rules and algorithms and applies machine learning (ML) tools.

In addition, an NLP engineer solves tasks of analysing and extracting information from texts, including ML methods. However, his tasks may not be limited to machine learning, as some of them require advanced knowledge of mathematics, linguistics and algorithm theory.

And of nlp courses, an NLP engineer should be a good programmer. In order to analyse and extract data from texts, you need not only to answer a lot of engineering challenges, but also to be able to prepare such data correctly.

In 2017, there was a revolution in the field of artificial intelligence and machine learning. The neural network architecture "transformer" appeared. It allowed to achieve incredible results in solving tasks of automated text data processing.

NLP-engineers got tools that in a short period of time significantly improved the quality of analysing unstructured information.

Learning Outcomes

Profile skills, without which the specialist will not be able to fulfil the assigned tasks:

Knowledge of the profile mathematical base.

Basic understanding of the English language (morphology, semantics, cases).

Knowledge of programming at the middle level and above.

Knowledge of Python, especially for NLP-engineer.

Ability to find the simplest solution - it is always the best.

Understanding of machine learning algorithms: neural networks, clustering algorithms, logistic regression.

Knowledge of industrial development languages: C++, C#, Java.

Personal qualities allow you to perform work nlp online courses tasks efficiently and move up the career ladder.

Career Pathways and Enrollment Details

NLP jobs in most cases require a major in computer science, computational maths, physics or related fields. Sometimes at least a Master's degree or a specialisation.

But there are other options: for example, nlp deep learning courses. For this you need to fill in an application form on the website and you are already a student. Don't waste time, join machine learning nlp courses now.

The pool of work in the natural language based neural network training profession depends directly on the specific business objective. For example, a large marketplace wants a query processing system to understand human-entered text and show the right product. In this case, an NLP engineer will proceed after neuro linguistic programming courses as follows:

create an algorithm that will process and categorise user queries;

configure the system so that it automatically recognises and enriches natural language queries;

train the model based on real queries;

use hadoop infrastructure to work with big data.

A profession in machine learning and natural language processing involves a combination of three components. The specialist should have a deep knowledge of mathematics and statistics, be able to program at a high level, and have an understanding of linguistics. The NLP Engineer profession is quite new and not all employers separate it from a Machine Learning Engineer (ML Engineer), although the specifics of work and knowledge of these specialists can be very different!