Month: December 2019

Categories
Machine Learning and Deep Learning

What is the Training Data?

Training Data

Machines are replacing humans in routine and manual jobs because of the faster processing speed and storing knowledge advantage they have over humans. One can even leverage their speed and turn them into intelligent machines. Here is where the Training data comes into the picture. By feeding them with relevant data, machines can be trained to mimic the human brain and learn to process information.

Training data even though is a simple concept, forms the basis to the way cutting-edge technologies like machine learning and deep learning programs work. It is an initial dataset that helps a program or an algorithm find relationships, understand, learn and produce sophisticated results.

The performance of the ML and DL models depends on the quality and quantity of the training data.

Why Training Data Matters?

One can describe training data as well-structured or labeled data that helps to sharpen your ML models.  You will require vast amounts of data to train your models with high accuracy.

A great model requires training data at a large scale and has to be labeled in a way that will work for training your algorithm or model. By feeding the self-driving car models with a picture of the road won’t be enough. They should be fed with labeled images where every object such as a street sign, vehicle, pedestrian and more have to be annotated.

In case of projects that require sentiment analysis, the algorithm has to be fed with labeled data that will help it to understand sarcasm or slang.

How to collect Training Data?

Data Labeler can be a good partner in your quest for training data. We have the expertise and experience in labeling millions of images and videos daily for some of the top innovative companies in the world.

Whether you are looking for text, image, video or any kind of data annotation services, we are here to help you in collecting world-class training data for any industry.

From autonomous vehicles and drones to agriculture, retail and sports analytics, we are adept at supporting all image and video annotation types. We specialize in the following:

  1. Bounding Box Annotation
  2. Polygonal Annotation
  3. Semantic Segmentation
  4. Cuboid Annotations
  5. Line annotation
  6. Text annotation
  7. Select & Multi-select annotation

Looking for a FREE consultation? Reach out to us at sales@datalabeler.com for top-quality data labeling services.

Categories
Natural Language Processing

What is Natural Language Processing (NLP) and What are its Uses?

Natural Language Processing

Natural Language Processing is a branch of Artificial Intelligence that enables the machines to read, understand and interpret the human language. Its main focus lies in the interaction between human language and Data Science.

Most of the techniques used in NLP depend on Machine Learning and Deep Learning to extract value from human language.

How NLP Works?

The first step in NLP depends on the type of application being used. In the case of voice-based systems, the first step involves the translation of words into text mainly using Hidden Markov Models (HMM). HMM involves usage of math models to understand what you said and translate into text which is then processed by the NLP system.

The next step involves understanding the context and the language by breaking every part of the sentence into its part of speech. A series of coded grammar rules that depend on algorithms are used for this step. These algorithms use statistical ML to help the NLP system understand the context of the word.

In the case of other scenarios where speech-to-text is not involved, the NLP system skips the first step and moves directly into interpreting words using grammar rules and algorithms.

NLP uses two main techniques for understanding human language; Syntax and Semantic analysis.

Syntax involves the arrangement of words to make sense grammatically. Syntax analysis enables NLP to derive meaning from a language based on grammatical rules.

Some of the syntax techniques include the following;

  • Parsing – Analyzing a sentence for grammar
  • Sentence breaking – Placing sentence boundaries for large texts
  • Word Segmentation – Dividing a large piece of text into smaller units
  • Morphological Segmentation – Dividing words into groups
  • Stemming – Dividing words with inflection to its root forms

The semantic analysis involves the extraction of exact meaning from the text. It helps the NLP system to understand the meaning and structure of sentences and to interpret human language logically.

NLP uses the following semantic techniques to understand sentences:

  • Sense Disambiguation – Deriving the meaning of a word using its context
  • Named Entity Recognition – Helps to identify the words that can be categorized into groups
  • Natural Language Generation – Usage of a database to extract semantics behind words

Common Uses of NLP

Chatbots

NLP can help improve the chatbots by training them for a particular behavior before deploying them. Chatbots use NLP algorithms for answering customer queries. These algorithms help the chatbots to understand a customer query and answer to those queries automatically in real-time.

Sentiment Analysis

Sentiment Analysis is a common application of NLP that can determine the positive or the negative polarity of a text. It can be used to classify reviews of a company or its products or poll customer’s opinion based on their social media posts and comments. This helps to provide customer insights on products or services.

NLP cannot single-handedly perform this task, it requires integration with ML and DL to perform back-end computation and data analytics to understand the data on a large scale.

Email Assistant

Grammar and spell check, auto-correct and auto-complete are some of the everyday use cases of NLP. Email filtering that keeps the spam mails away also uses NLP to determine the type of emails to keep in your inbox and sort out the spam mails.

About Data Labeler

Data Labeler specializes in providing high-quality data labeling services and is one of the top data annotation companies in New Jersey. Are you for looking Machine Learning Training Data to train your AI-based algorithms and models? Reach out to us at sales@datalabeler.com for top-quality data labeling services.

Categories
Data Labeling

Data Labeling for Livestock Monitoring

Data Labeling for Livestock Monitoring

The client is one of the largest cattle companies in the world!

The Client Requirement

During the process of letting the cattle out for grazing, the company is faced with the task of manually counting the number of cattle being let out and do the same when they come back. It has become a challenge for the client as they are dealing with a large number of cattle in the range of 1000+. The main challenge for the client is to make sure all the cattle have been accounted for without any errors as each count makes up for thousands of dollars.

How did Data Labeler Help?

The project for cattle recognition included several stages:

  • Data Labeler collected the footage of the cattle in various parts of the counting process.
  • Image classification was performed to classify the species of the animal.
  • Annotation localization helped to place the bounding boxes over the animals.
  • With annotation classification, the team was able to add species labels to each annotation.
  • The labeled dataset was then used by the client to train an algorithm to identify the cattle and count them when they are let out for grazing or let in.

The Result

  • The team could meet the client’s quality benchmark by achieving 100% accuracy throughout the project.
  • This helped the client to train the model with precision.
  • The challenge faced by the client with the traditional method of counting the cattle was overcome with the trained ML model.
  • It also eliminated any chances of human error thereby achieving accuracy while counting cattle.

Are you looking for similar services and have a huge database of images? Need help with data annotation, tagging or any labeling services, contact Data Labeler today for efficient and affordable data labeling services.