data science

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

Is TensorFlow a good fit for model optimisation?

Reading Time: 2 minutes In the realm of AI, a great deal of consideration is optimising training. There is a lot less information out there on optimising models. However serving models for forecast is the place where we make money out of ML. Without a doubt, the expense of serving forecasts might be a central point in the all out profit from speculation for a ML application. In this Continue Reading

Apache Airflow Operators and Tasks

Reading Time: 3 minutes Context: What is Airflow? Airflow is a free to use and open-source tool developed by Apache that is used to manage workflows Most popular and one of the best workflow management systems out there with great community support. What is a DAG ? DAG stands for Directed Acyclic Graph Directed means the flow is one directional Acyclic means the flow will never come back to Continue Reading

How To Find Correlation Value Of Categorical Variables.

Reading Time: 4 minutes Hey folks, In this blog we are going to find out the correlation of categorical variables. What is Categorical Variable? In statistics, a categorical variable has two or more categories.But there is no intrinsic ordering to the categories. For example, a binary variable(such as yes/no question) is a categorical variable having two categories (yes or no), and there is no intrinsic ordering to the categories. Continue Reading

Pandas for Data Analysis

Reading Time: 4 minutes Why Pandas for data Analysis? Real ‘raw’ data needs a lot of ‘wrangling’ operations before it can be ready for dissection by a data scientist one of the popular tools for data wrangling in python is Pandas. Because of the availability of widespread packages of Pandas for almost every possible function. The library Pandas is one such package that makes life easier especially for data analysis. Through Continue Reading

Machine-Learning-in-capital-market

Implementing Machine Learning in Capital Markets

Reading Time: 4 minutes When the COVID-19 outbreak became a global pandemic, financial-markets volatility hit its highest level in more than a decade, amid pervasive uncertainty over the long-term economic impact. Calm has returned to markets in recent months, but volatility continues to trend above its long-term average. Amid persistent uncertainty, financial institutions are seeking to develop more advanced quantitative capabilities to support faster and more accurate decision making. Continue Reading

Analysis of campus placement dataset using decision tree

Reading Time: 3 minutes KNIME Analytics Platform is open-source software for creating data science applications and services. Intuitive, open, and continuously integrating new developments, KNIME makes understanding data and designing data science workflows and reusable components accessible to everyone. With KNIME Analytics Platform, you can create visual workflows with an intuitive, drag and drop style graphical interface, without the need for coding. Hello, folks! In this blog, we will analyse the Campus placement data Continue Reading

ICC Test Cricket Data Analysis using KNIME

Reading Time: 4 minutes KNIME Analytics Platform is open-source software for creating data science applications and services. Intuitive, open, and continuously integrating new developments, KNIME makes understanding data and designing data science workflows and reusable components accessible to everyone. With KNIME Analytics Platform, you can create visual workflows with an intuitive, drag and drop style graphical interface, without the need for coding. Hello, folks! In this blog, we will analyse Continue Reading

Linear Regression with Knime

Reading Time: 5 minutes Linear Regression is perhaps one of the most well known and well -understood algorithms in Statistics and Machine Learning. It tries to find a relationship between the independent and dependent continuous variables by determining a linear equation of the form Y = b0 + b1*x1 + b2*x2 + ….. Here, the x values represent the independent variables, b values are the coefficients of the independent Continue Reading

MachineX: Run ML model prediction faster with Hummingbird

Reading Time: 3 minutes In this blog, we will see how to make our machine learning model’s prediction faster with a recently open-sourced library Hummingbird. Nowadays, we can see a lot of frameworks for deploying or serving the machine learning model into production. As a result, It is a headache for a data scientist to choose between these frameworks, keeping in mind how their model either Sklearn or LightGBM Continue Reading

Knime Analytics Platform: A dream for a data scientist

Reading Time: 3 minutes In this blog, we are going to see, what is the Knime analytics platform and its important features to create an analytics workflow in an easy way. Introduction to Knime Analytics Platform KNIME is a platform built for powerful analytics on a GUI based workflow. This means you do not have to know how to code to be able to work using KNIME and derive Continue Reading

COVID-19 Detector: Detecting Corona from X-Ray

Reading Time: 4 minutes A web application using deep learning to help medical practitioners to detect COVID-19 symptoms with chest x-rays. COVID-19 disease, caused by the SARS-CoV-2 virus, was identified in December 2019 in China and declared a global pandemic by the WHO(World Health Organization) on 11 March 2020. The disease first originated in Wuhan, China and since then it has spread globally across the world affecting more than 200 countries. Coronavirus disease 2019 (COVID-19) Continue Reading

MachineX: performance metrics for Model Evaluation

Reading Time: 6 minutes In this blog, we are going to see how to choose the right metrics for model evaluation in different kinds of applications. There are different metric categories based on the ML model/application, and we are going to cover the popular metrics used in the following problems: Classification Metrics (accuracy, precision, recall, F1-score, ROC, AUC) Regression Metrics (MSE, MAE) there are more metrics like Computer Vision Continue Reading