ML, AI and Data Engineering

Music Genre Classification: Identification Of The Audio

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

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

Complete Guide to Single Layer Perceptron with Implementation

Reading Time: 4 minutes To understand the single-layer perceptron, it is important to understand the artificial neural network (ANN). An artificial neural network is an information processing system whose mechanism is inspired by the function of biological neural circuits. Artificial neural networks have many interconnected computing units. The schematic diagram of the artificial neural network is as follows. This figure shows that the hidden entity is communicating with the 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

Deploy modes in Apache Spark

Reading Time: 2 minutes Spark is an open-source framework engine that has high-speed and easy-to-use nature in the field of big data processing and analysis. Spark has some built-in modules for graph processing, machine learning, streaming, SQL, etc. The spark execution engine supports in-memory computation that makes it faster and cyclic data flow and it can run either on cluster mode or standalone mode and can also access diverse 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

NLP using Tensorflow: A Small Guide

Reading Time: 3 minutes Natural Language Processing or NLP is now one of the most important machine learning techniques that one AI/ML practitioner should possess. It the current world we can see a vast use of NLP implementations. Such as text reading, number plate reading,email spam filtering, predictive text and so on. In this blog we are going to see some key things to know, in order to implement Continue Reading

Why Use MongoDB in Machine learning? And how to use MongoDB in Python?

Reading Time: 5 minutes In this blog, we will learn why to use MongoDB in Machine Learning. And how we can use MongoDB in Python using Pymongo. MongoDB is a document-oriented NoSQL database used for high-volume data storage. Instead of using tables and rows as in the traditional relational databases. MongoDB makes use of collections and documents. It is an open-source, cross-platform, document-oriented database written in C++. Installing MongoDB Continue Reading

Kubeflow: A Complete Solution to MLOps.

Reading Time: 5 minutes Hey Folks, In this blog we are going to put some light on Kubeflow, an open-source platform that enables us to orchestrate complicated workflows running on Kubernetes of machine learning pipelines. Kubeflow Emerges for ML Workflow Automation Many data scientists today find it burdensome to manually execute all of the steps in a machine learning workflow. Moving and transforming data, training models, then promoting them 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

Model Evaluation Metrics for Machine Learning Algorithms

Reading Time: 6 minutes When you build any Machine Learning model, all the audiences including the stakeholders always have only one question, what is the model performance? What are the model evaluation metrics? What is the accuracy of model? Model Evaluation metrics explains the performance of models. Evaluating your developed model helps you refine and improve your model. You keep developing and evaluating a model until you reach an Continue Reading