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Articles by Raghav Agrawal
Baltimore strong: The resiliency of cities
Like many other residents of Baltimore, I woke up on Tuesday morning to the news of the Francis Scott Key Bridge falling overnight when it was hit by a massive ship that was exiting the Port of Baltimore. It goes without saying that this was a devastating incident for the city, and our thoughts and prayers are especially with those who lost loved ones. The impetus for writing something really came after my surprise at my own visceral reaction to the news.
The sounds of Baltimore: Learning to listen
While running the risk of taking the name of this column too literally, it's time we talk about the sounds of Baltimore. While it may be famous for its crabs, Old Bay and Natty Bohs — its glistening harbor, picturesque parks and breath-taking sunsets — the voices of the city hold a special place in my heart. I grew up in Bombay (Mumbai), on the west coast of India, and was introduced to the sounds of a city in a bustling metropolis.
Cities should be made more walkable and pedestrian-friendly
A city gets its personality from its people — likewise, people are heavily influenced by where they call home. In the complexity of modern life, we often forget about this simple, symbiotic relationship — what we give to our city is what we get. In this light, making cities more walkable and pedestrian-friendly gives back to a city that has already given us so much.
End-to-End NLP Project on Quora Duplicate Questions
Advanced Data Science Github Machine Learning NLP Project Python Introduction Automation today is taking place in each sector. Every industry acquires different technological innovations and products to take charge of the market. And one of the leading technology which enjoys more attraction is NLP (Natural Language Processing).
Performing Analysis on WhatsApp chats
Data Analysis Github Intermediate Project Python Streamlit Introduction Machine learning projects always excite people and inspire them to learn more about them. But the Machine learning model works on data. Before model construction, we need to analyze and understand the data to identify the hidden patterns that come under the data analysis.
Building Customer Churn Prediction Model With Imbalance Dataset
Beginner Data Analysis Datasets Machine Learning Python Structured Data Introduction The digital revolution is taking place at a very fast pace. Data generation over the cloud is increasing in massive amounts regularly, and data being king in the digital era can win anything. The amount of data is insufficient until it does not reflect or we cannot find meaningful information that can drive business decisions.
Complete Guide to Ethereum Blockchain with Python
Beginner Blockchain Python Web 3.0 Introduction We have internet access in every corner of the country. Almost all businesses around us, like manufacturing, retail, consultancy, etc., are tryything about your surroundings, then the internet is the first choice we prefer. People’s experience over the web transforms daily, and demand constantly expands over time.
Build AI Web App using Azure Cognitive Services
Azure AzureML Computer Vision Image Image Analysis Object Detection Python This article was published as a part of the Data Science Blogathon. Introduction Web apps are the apps through which you cn showcase your solution or approach to the public at a mass level. Creating the model is not enough until it’s in use by people. When it comes to delivering the solution then, everyone comes with creating a website.
How to Deploy a Machine learning model on AWS EC2
This article was published as a part of the Data Science Blogathon. Introduction AWS is a cloud computing service that provides on-demand computing resources for storage, networking, Machine learning, etc on a pay-as-you-go pricing model. AWS is a premier cloud computing platform around the globe, and most organization uses AWS for global networking and data storage.
Complete Guide to run Machine learning on Spark using Spark MLLIB
This article was published as a part of the Data Science Blogathon. Introduction The digital transformation has given rise to the release of massive amounts of data each second, and companies’ servers are not that powerful to bear the load. It is tough to store and process a massive amount of data and more difficult when we have real-time or streaming data. When Hadoop came into the picture, then the companies need to use MapReduce, which only works in Java and needs to write many lines of code.
20 Most Asked Interview Questions of Machine Learning
Beginner Interviews Machine Learning This article was published as a part of the Data Science Blogathon. Introduction Cers, and computer vision engineers are more in-demand organizational roles. If you wish to apply and grab a job in the tech domain, it’s crucial to know common machine learning interview questions that recruiters ask.
Create Smart Contract Using Solidity Programming
Beginner Blockchain Technology This article was published as a part of the Data Science Blogathon. Introduction Blockchain is a decentralized, distributed public ledger that lets us collaborate and coordinate the members that do not trust each other to make a secure transaction. Many of you understand blockchain as a bitcoin, but bitcoin is a cryptocurrency that takes the help of blockchain technology to operate.
A Beginner's Guide to Geospatial Data Analysis
Datasets Intermediate Machine Learning This article was published as a part of the Data Science Blogathon. Introduction to Geospatial Data Analysis Geospatial data is any type of data that has certain geographic factors like latitude, longitude, etc. geographic component simply means a location or several locations that can take the form of simple points or more complex shapes describing lines, boundaries, or even elevation.
Data Analysis Project for Beginners Using Python
This article was published as a part of the Data Science Blogathon. Introduction Data Analysis is one major part that you must master before learning or diving into the machine learning algorithms section because data analysis is a process to explore the data to a better understanding of data. Data Analysis is a core part of any data science or machine learning project which almost takes 70 to 80 per cent of the time of the complete project lifecycle.
Beginners Guide to Data Warehouse Using Hive Query Language
This article was published as a part of the Data Science Blogathon. Introduction Have you ever wondered how big IT giants store and process huge amounts of data? Different organizations make use of different databases liresults. This led to the creation of Hive and hive query language which we are going to explore in this article. What is Hive?
Music Genre Classification Project Using Machine Learning Techniques
This article was published as a part of the Data Science Blogathon. Hello, and welcome to a wonderful article on audio classification. Audio classification is an Application of machine learning where different sound is categorized in certain categories. In our previous blog, we have studied Audio classification using ANN and build a model from scratch. Almost all data science enthusiasts want attractive and eye-catching data science projects on their resume and Audio processing is one such topic.
Implementing Audio Classification Project Using Deep Learning
This article was published as a part of theย Data Science Blogathon. where we will be exploring learnings for audio and sound classification using Machine learning and deep learning. It is amazing and interesting to know-how machines are capable to understand human language, and responding in the same human language.
Lambda Functions in Python | Map, Filter, and Reduce
This article was published as a part of the Data Science Blogathon. Introduction Hello, and welcome to the beautiful article where we will learn and discuss various facts related to python Lambda functions. Python is a dynamic yet straightforward typed language, and it provides multiple libraries and in-built functions.
Machine Learning Techniques for Text Representation in NLP
This article was published as a part of the Data Science Blogathon. Introduction Natural Language Processing is a branch of artificial intelligence that deals with human language to make a system able to understand and respond to language. Data being the most important part of any data science project should always be represented in a way that helps easy understanding and modeling.
Complete Guide on Rest API with Python and Flask
This article was published as a part of the Data Science Blogathon. , I hope you are fine. I want to welcome you to a beautiful article on creating a REST API using Flask. In one of our previous articles, we have learned the basics of Flask and how to set it. We have made one complete end-end machine learning project with Flask. You can access the previous article from here.
Multiple Time Series Model Using Apache Spark and Facebook Prophet
This article was published as a part of the Data Science Blogathon. Introduction Let’s say you are a large retailer like Walmart, D-Mart, and you may deal with thousands and thousands of products and each product will have a different sale cycle.
Complete Guide to Anomaly Detection with AutoEncoders using Tensorflow
This article was published as a part of the Data Science Blogathon. critical in machine learning use cases. Data Compression is a big topic used in computer vision, computer networks, and many more. Data compression represents our input into a more miniature representation that we recreate to quality. This is a more miniature representation of what would be passed around, and when an original one is required, they will reconstruct it from a more miniature model.
Anomaly Detection Model on Time Series Data in Python using Facebook Prophet
This article was published as a part of the Data Science Blogathon Introduction Time series data is the collection of data at specific time intervals like on an hourly basis, weekly basis. Stock market data, e-commerce sales data is perfect example of time-series data. Time-series data analysis is different from usual data analysis because you can split and create samples according to randomness in data analysis and preprocessing.
Complete NLP Landscape from 1960 to 2020
This article was published as a part of the Data Science Blogathon Hello and welcome to the interesting article that revolves around a very cheesy and hot topic in trending technologies which is NLP(Natural Language Processing). In this article, we will learn what exactly is NLP, what makes it complex to learn and what challenges do we face while solving any NLP problem statement.
Python String Data Structure
This article was published as a part of the Data Science Blogathon. The string is one standard Data type in Python. You will find string data type in every application programming language like Java, Python, C++ because while developing an application you need to talk to the user and it is done in strings.
A Complete Beginner-Friendly Guide to SQL for Data Science
This article was published as a part of the Data Science Blogathon. SQL stands for Structured Query Language which is used to deal with Relational Databases to query from and manipulate databases. In the field of Data Science most of the time you are supposed to fetch the data from any RDBMS and run some simple and complex queries to retrieve and extract data in different ways to understand relationships or irregularities that exist in the dataset.
How to Deploy Machine Learning(ML) Model on Android
This article was published as a part of the Data Science Blogathon only not the case but making it able to community to use is important otherwise the model is up to you only. When it is able to serve then you came to know the feedback and improvements needed to improve it. Implementing a Machine learning model in a jupyter Notebook is a very easy task. And 90 percent of times when any data science practitioner deploys his problem statement it is in the form of a website.
Laptop Price Prediction in Machine Learning
This article was published as a part of the Data Science Blogathon. that can make a future prediction based on past data. If you are a data science enthusiast or a practitioner then this article will help build your own end-to-end machine learning project from scratch. There are various steps involved in building a machine learning project but not all the steps are mandatory to use in a single project, and it all depends on the data.
A Comprehensive Guide on using Flask for Data Science
Overview of Flask to create a machine learning model for the specific problem but presenting your solution to the audience, to a client so they can give you new data is also important because your aim is to create an impact in society with your solution, and all will happen when you deploy your solution to cloud and for this, you need to take help of some web framework and Flask is one micro web framework that helps you to take your solution to your audience with easy steps.
Beginner's Guide on How to Prepare Dataset using Web Scraping
This article was published as a part of the Data Science Blogathon like databases, online repositories, APIs, survey forms, and many others. But when we want to extract any internet site data when no means of API is there then the best alternative left is Web Scraping. In this article, you will learn about web scraping in brief and see how to extract data from websites with a hands-on demonstration with python. We will be covering the following topics.
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