自然语言处理培训,NLP培训,Natural Language Processing培训




代码 名字 时长 概览
nlp Natural Language Processing 21小时 This course has been designed for people interested in extracting meaning from written English text, though the knowledge can be applied to other human languages as well. The course will cover how to make use of text written by humans, such as  blog posts, tweets, etc... For example, an analyst can set up an algorithm which will reach a conclusion automatically based on extensive data source.
python_nltk Natural Language Processing with Python 28小时 This course introduces linguists or programmers to NLP in Python. During this course we will mostly use nltk.org (Natural Language Tool Kit), but also we will use other libraries relevant and useful for NLP. At the moment we can conduct this course in Python 2.x or Python 3.x. Examples are in English or Mandarin (普通话). Other languages can be also made available if agreed before booking.
Neuralnettf Neural Networks Fundamentals using TensorFlow as Example 28小时 This course will give you knowledge in neural networks and generally in machine learning algorithm,  deep learning (algorithms and applications). This training is more focus on fundamentals, but will help you choosing the right technology : TensorFlow, Caffe, Teano, DeepDrive, Keras, etc. The examples are made in TensorFlow.
aitech Artificial Intelligence - the most applied stuff - Data Analysis + Distributed AI + NLP 21小时 This course is aimed at developers and data scientists who wish to understand and implement AI within their applications. Special focus is given to Data Analysis, Distributed AI and NLP.
nlpwithr NLP: Natural Language Processing with R 21小时 It is estimated that unstructured data accounts for more than 90 percent of all data, much of it in the form of text. Blog posts, tweets, social media, and other digital publications continuously add to this growing body of data. This course centers around extracting insights and meaning from this data. Utilizing the R Language and Natural Language Processing (NLP) libraries, we combine concepts and techniques from computer science, artificial intelligence, and computational linguistics to algorithmically understand the meaning behind text data. Data samples are available in various languages per customer requirements. By the end of this training participants will be able to prepare data sets (large and small) from disparate sources, then apply the right algorithms to analyze and report on its significance. Audience     Linguists and programmers Format of the course     Part lecture, part discussion, heavy hands-on practice, occasional tests to gauge understanding
mldlnlpintro ML、DL與NLP入門與進階大綱 14小时 The aim of this course is to provide a basic proficiency in applying Machine Learning methods in practice. Through the use of the Python programming language and its various libraries, and based on a multitude of practical examples this course teaches how to use the most important building blocks of Machine Learning, how to make data modeling decisions, interpret the outputs of the algorithms and validate the results. Our goal is to give you the skills to understand and use the most fundamental tools from the Machine Learning toolbox confidently and avoid the common pitfalls of Data Sciences applications.
pythontextml Python:用文本进行机器学习 21小时 在这一由讲师引导的现场培训中,参与者将学习如何使用正确的机器学习和NLP(自然语言处理)技术从基于文本的数据中提取价值。 在本次培训结束后,参与者将能够: 用高质量、可重用的代码解决基于文本的数据科学问题 运用scikit-learn的不同方面(分类、聚类、回归、降维)来解决问题 使用基于文本的数据建立有效的机器学习模型 创建一个数据集并从非结构化文本中提取特征 用Matplotlib可视化数据 构建和评估模型以获得洞察力 解决文本编码错误 受众 开发人员 数据科学家 课程形式 部分讲座、部分讨论、练习和大量实操
nlg Python for Natural Language Generation 21小时 Natural language generation (NLG) refers to the production of natural language text or speech by a computer. In this instructor-led, live training, participants will learn how to use Python to produce high-quality natural language text by building their own NLG system from scratch. Case studies will also be examined and the relevant concepts will be applied to live lab projects for generating content. By the end of this training, participants will be able to: Use NLG to automatically generate content for various industries, from journalism, to real estate, to weather and sports reporting Select and organize source content, plan sentences, and prepare a system for automatic generation of original content Understand the NLG pipeline and apply the right techniques at each stage Understand the architecture of a Natural Language Generation (NLG) system Implement the most suitable algorithms and models for analysis and ordering Pull data from publicly available data sources as well as curated databases to use as material for generated text Replace manual and laborious writing processes with computer-generated, automated content creation Audience Developers Data scientists Format of the course Part lecture, part discussion, exercises and heavy hands-on practice
opennlp OpenNLP for Text Based Machine Learning 14小时 The Apache OpenNLP library is a machine learning based toolkit for processing natural language text. It supports the most common NLP tasks, such as language detection, tokenization, sentence segmentation, part-of-speech tagging, named entity extraction, chunking, parsing and coreference resolution. In this instructor-led, live training, participants will learn how to create models for processing text based data using OpenNLP. Sample training data as well customized data sets will be used as the basis for the lab exercises. By the end of this training, participants will be able to: Install and configure OpenNLP Download existing models as well as create their own Train the models on various sets of sample data Integrate OpenNLP with existing Java applications Audience Developers Data scientists Format of the course Part lecture, part discussion, exercises and heavy hands-on practice
python_nlp Natural Language Processing with Deep Dive in Python and NLTK 35小时 By the end of the training the delegates are expected to be sufficiently equipped with the essential python concepts and should be able to sufficiently use NLTK to implement most of the NLP and ML based operations. The training is aimed at giving not just an executional knowledge but also the logical and operational knowledge of the technology therein.  
textsum 用Python进行文本摘要 14小时 在Python机器学习中,文本摘要功能可以读取输入文本并生成文本摘要。这个功能可以从命令行或从Python API / 库中获得。一个令人兴奋的应用是执行摘要的快速创建;这对在做报告和演讲前需要审阅大量文本数据的组织特别有用。 在这一由讲师引导的现场培训中,学员将学习使用Python创建一个简单的可自动生成输入文本摘要的应用程序。 在本次培训结束后,学员将能够: 使用一个命令行工具来总结文本。 使用Python库设计和创建文本摘要代码。 评估三个Python摘要库:sumy 0.7.0、psisummarization 1.0.4、readless 1.0.17 受众 开发人员 数据科学家 课程形式 部分讲座、部分讨论、练习和大量实操
dlfornlp Deep Learning for NLP (Natural Language Processing) 28小时 Deep Learning for NLP allows a machine to learn simple to complex language processing. Among the tasks currently possible are language translation and caption generation for photos. DL (Deep Learning) is a subset of ML (Machine Learning). Python is a popular programming language that contains libraries for Deep Learning for NLP. In this instructor-led, live training, participants will learn to use Python libraries for NLP (Natural Language Processing) as they create an application that processes a set of pictures and generates captions.  By the end of this training, participants will be able to: Design and code DL for NLP using Python libraries Create Python code that reads a substantially huge collection of pictures and generates keywords Create Python Code that generates captions from the detected keywords Audience Programmers with interest in linguistics Programmers who seek an understanding of NLP (Natural Language Processing)  Format of the course Part lecture, part discussion, exercises and heavy hands-on practice


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Word2vec是一个特别有效的计算预测模型,用于从原始文本中学习单词嵌入。 在这个由教师领导的现场培训中,参与者将学习如何使用Python从头开始构建自己的NLG系统,以生成高质量的自然语言文本。 在这次培训结束后,参与者将能够准备不同来源的数据集(大小),然后应用正确的算法分析和报告其意义。 这个培训更关注基础知识,但是会帮助你选择正确的技术:TensorFlow,Caffe,Teano,DeepDrive,Keras等。 在这个由讲师引导的实时培训中,参与者将学习使用Python创建一个简单的应用程序,自动生成输入文本的摘要。