Artificial intelligence

A Simple Guide to Data Preprocessing in Machine Learning

Reading Time: 5 minutes Machine learning algorithms are completely data-dependent as they are the most important aspect of enabling model training. On the other hand, if you don’t understand this data before feeding it to the ML algorithm, the machine becomes useless. Simply put, you always need to provide the right data due to that preparing data in machine learning with the appropriate scale, format, and meaningful attributes for Continue Reading

A Complete Guide To Recurrent Neural Network

Reading Time: 5 minutes Recurrent neural networks are a type of deep learning-oriented algorithm that follows a sequential approach. Neural networks always assume that each input and output is independent of all other layers. This type of neural network is recurrent neural network because it performs mathematical calculations in a sequence. Neural networks imitate the function of the human brain in the fields of AI, machine learning, and deep Continue Reading

Make better decisions with Google Cloud Document AI

Reading Time: 3 minutes Nearly all business processes today begin, include or end with a document. Most companies are sitting on the document goldmine. Thinking of which some are PDFs, emails, customer feedback, patents, contracts, technical documents, sensitive documents, HR files and the list goes on. These documents are only going to grow with time. Making sense of each document is difficult since a lot of these documents are Continue Reading

Explore OpenCV & Why Do We Need To Know About It?

Reading Time: 4 minutes OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning software library. It was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in commercial products. Being a BSD-licensed product, OpenCV makes it easy for businesses to utilize and modify the code. OpenCV OpenCV is the huge open-source library for computer vision, Continue Reading

Why Computer Vision Had Been So Popular Till Now?

Reading Time: 3 minutes What is computer vision? Computer vision(CV) is the field of computer science that focuses on creating digital systems that can process, analyze, and make sense of visual data (images or videos) in the same way that humans do. The concept of computer vision is based on teaching computers to process an image at a pixel level and understand it. Technically, machines attempt to retrieve visual Continue Reading

Introduction to Ensemble Learning

Reading Time: 4 minutes Ensemble methods are techniques that create multiple models and then combine them to produce improved results. Ensemble learning usually produces more accurate solutions than a single model would. This has been the case in a number of machine learning competitions and, where the winning solutions used ensemble methods. Ensemble methods You must ensure that your models are independent of one another and when creating a Continue Reading

Introduction to Machine Learning Lifecycle

Reading Time: 3 minutes Building a machine learning model is an iterative process. For a successful deployment, most of the steps are replicated several times to achieve optimal results. The model must sustain after deployment and adapted to changing environment. Let’s look at the details of the lifecycle of a machine learning model. What is machine learning lifecycle? The machine learning lifecycle is the process of developing, deploying, and Continue Reading

Natural Language Understanding(NLU)

Reading Time: 4 minutes What is NLU? One easy way to understand NLU is by looking at available consumer services and business products that model natural language understanding. For example, Apple’s Siri or Amazon’s Alexa performs natural language understanding work in the context of hearing and deciphering user inputs. A similar natural language understanding engine is built into Amazon “Lex,” an enterprise service for building machine learning platforms. By Continue Reading

An Intro to Chatbot Development using RASA

Reading Time: 4 minutes What is RASA? RASA is an open-source chatbot framework based on machine learning. With the help of it, we can easily create highly accurate and sophisticated chatbots and can easily integrate these chatbots with our website, Telegram, Facebook, etc. Before we get into it, let’s look into some simple concepts that we should know while creating a chatbot. Query A query is the user message Continue Reading

Let us know about TensorFlow Extended (TFX) components and Libraries?

Reading Time: 3 minutes In this blog, we will be learning about Tensorflow Extended (TFX) components and libraries. TFX is a Google-production-scale machine learning (ML) platform based on TensorFlow. It provides a configuration framework and shared libraries. Moreover, to integrate common components needed to define, launch, and monitor your machine learning system. How Tensorflow Extended (TFX) came up? Since the time Google has publicized Tensorflow, its application in Deep Continue Reading

Cloud Data Loss Prevention (DLP): Part-2

Reading Time: 2 minutes Google Cloud Platform’s Data Loss Protection API provides a service that can make organizations manage sensitive data, including detecting and redaction, masking, and tokenizing such data. This can help organizations comply with regulations such as GDPR, and reduce the risk of data exposure and data breaches. Such as a name, email address, telephone number, identification number, or credit card number. In the previous blog Cloud Data Loss Continue Reading

A Simple Guide to OCR using Pytesseract

Reading Time: 2 minutes What is OCR OCR is an acronym for optical character recognition. It is a widespread technology to recognize text inside images, such as scanned documents and photos. OCR technology is used to convert virtually any kind of image containing written text (typed, handwritten, or printed) into machine-readable text data.  OCR using Pytesseract Python-tesseract is a wrapper for Google’s Tesseract OCR engine. It can read any Continue Reading

Text Data Vectorization Techniques in Natural Language Processing

Reading Time: 6 minutes Features in any Machine Learning algorithms are generally numerical data on which we can easily perform any mathematical operations. But Machine Learning algorithms cannot work on raw text data. Machine Learning algorithms can only process numerical representation in form of vector(matrix) of actual text. For converting textual data into numerical representation of features we can use the following text vectorization techniques in Natural Language Processing. Continue Reading