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ML, AI and Data Engineering

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Google Cloud Platform: Migrating Data to New Schemas on Big Query Using Dataflow

AI, GCP, ML, AI and Data Engineering, , , , , , ,

Reading Time: 6 minutes Migrating data on Google Cloud BigQuery may seem like a straightforward task, until you run into having to match old data to tables with different schemas and data types. There are many approaches you can take to moving data, perhaps using SQL commands to transform the data to be compatible with the new schema. However, SQL has limitations as a programming language, being a query-centric Continue Reading

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Know how Computer Vision and Augmented Reality overlap each other?

AI, ML, AI and Data Engineering, python, , , ,

Reading Time: 2 minutes To understand the overlapping of Computer Vision and Augmented Reality, Let’s understand what is computer vision, augumented reality and virtual reality. Computer Vision Augmented Reality Virtual Reality A direct comparison of Augmented Reality and Virtual Reality Application of Augmented Reality and Computer Vision Augmented Reality and Computer Vision in Autonomous Cars Security Monitoring with Augmented Vision and Computer Vision Augmented Reality and Computer Vision in Continue Reading

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Build easy conversational AI – GCP Dialogflow

ML, AI and Data Engineering, Studio-Scala, , ,

Reading Time: 3 minutes Dialogflow is a GCP framework that enables users to develop easy human-computer interaction technologies that can support Natural Language Processing (NLP). Basically, Dialogflow handles the job of translating natural language to machine-readable data using machine-learning models trained by your examples. Why use GCP Dialogflow A few reasons to use Dialogflow are – Building Blocks of GCP Dialogflow AGENTS The agent is basically your entire chatbot Continue Reading

Artificial Intelligence & MarkLogic: An Wonderful Architecture

Database, Java, java11, MarkLogic, ML, AI and Data Engineering, Tech Blogs, ,

Reading Time: 3 minutes Introduction Automation is a crucial part of the Artificial Intelligence cycle. It allows organizations to perform tasks that require human input and improves tradecraft. This also increases efficiency in order to keep pace with changing technologies and requirements. And MarkLogic is providing some extra benefits in implementing AI processes. MarkLogic has its own optimized algorithms and implementations of some AI methodologies. Achieved due to its Continue Reading

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Let us know what is TensorFlow Lite Task Library

AI, ML, AI and Data Engineering, , , ,

Reading Time: 2 minutes TensorFlow Lite is a framework of software packages that enables ML training locally on the hardware. This on-device processing and computing allow developers to run their models on targeted hardware. The hardware includes development boards, hardware modules, and embedded and IoT devices. TensorFlow Lite Task Library contains a useful and powerful set of interfaces. That helps us handle most of the pre-processing and post-processing logic Continue Reading

Let’s know how to Convert the TensorFlow model to the TensorFlow Lite model

ML, AI and Data Engineering, , ,

Reading Time: 2 minutes TensorFlow Lite is TensorFlow’s lightweight solution for mobile and embedded devices. It allows you to run machine learning models on edge devices with low latency, eliminating the need for a server. After the development of the TensorFlow model, we can convert the same to a more efficient and smaller version by converting it into a Tflite model format. Let’s explore how. Conversion Workflow of TensorFlow Lite Continue Reading

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MarkLogic And Machine Learning: Easy way of ML

Database, Java, MarkLogic, ML, AI and Data Engineering, Tech Blogs,

Reading Time: 6 minutes Introduction Machine learning is a subfield of computer science. Used to deal with the construction of artificial intelligence systems that can learn without being explicitly programmed. It has been applied in many areas such as data analysis, pattern recognition, and understanding human behavior. MarkLogic combines database internals, search-style indexing, and application server behavior into a unified system. It uses XML and JSON documents along with Continue Reading

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What Are Transformers In NLP And It’s Advantages

AI, Artificial intelligence, ML, AI and Data Engineering

Reading Time: 4 minutes NLP’s Transformer is a new architecture that aims to solve tasks sequence-to-sequence while easily handling long-distance dependencies. Computing the input and output representations without using sequence-aligned RNNs or convolutions and it relies entirely on self-attention. Lets look in detail what are transformers. The Basic Architecture In general, the Transformer model is based on the encoder-decoder architecture. The encoder is the gray rectangle on the left Continue Reading

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Big Query DML Statements Technique: A small Guide

AI, Big Data and Fast Data, Database, GCP, ML, AI and Data Engineering,

Reading Time: 3 minutes In this blog we are going to learn about some of the key Big Query DML statements. Data plays an integral part in any organisation. With the data-driven nature of modern organisations, almost all businesses and their technological decisions are based on the available data. Let’s assume that we have an application distributed across multiple servers in different regions of a cloud service provider, and Continue Reading

Best Approach For Resume screening by Machine Learning-Part 1

Artificial intelligence, ML, AI and Data Engineering, , , , ,

Reading Time: 3 minutes Introduction Resume screening is the process of determining whether a candidate is qualified for a role based on his or her education, experience, and other information captured on their resume. It’s a form of pattern matching between a job’s requirements and the qualifications of a candidate based on their resume. The goal of screening resumes is to decide whether to move a candidate forward – Continue Reading

All You Need To Know About Decision Tree Algorithm

ML, AI and Data Engineering, , , , , , ,

Reading Time: 5 minutes In this blog, we are going to discuss Decision Tree algorithm, a supervised algorithm which can be used to solve both regression and as well as classification problem too. A classification algorithm, in general, is a function that weighs the input features so that the output separates one class into positive values and the other into negative values. Introduction to Decision Tree Algorithm A decision tree Continue Reading

Music Genre Classification: Identification Of The Audio

AI, ML, AI and Data Engineering, , , , ,

Reading Time: 4 minutes In this blog, we will discuss and build a music genre classification model to predict the genre/label of the music/song. Music Genre Classification Today we will build a Tensorflow sequential model to automatically classify different musical genres from the given input audio files. Dataset To train our ml classifier model to predict the audio’s genre/label, we will use the GTZAN Dataset.You can download the dataset Continue Reading

A Simple Guide to Data Preprocessing in Machine Learning

AI, Artificial intelligence, ML, AI and Data Engineering, python

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

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