Sat.Aug 21, 2021 - Fri.Aug 27, 2021

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Python Tutorial: Working with CSV file for Data Science

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon Source Intro: In this article, I will walk you. The post Python Tutorial: Working with CSV file for Data Science appeared first on Analytics Vidhya.

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Can AI Outsmart Humans? 5 times AI found unexpected solutions

Dlabs.ai

When developers designed a self-driving car simulator to ‘go fast and drive safe,’ they didn’t expect what came next. The algorithm at the wheel ordered the car to speed round and round on the spot. The strategy was brilliant because, with the wheels spinning and passers-by in no danger, the simulator had followed its instructions to the letter. It’s just — the vehicle would never reach a destination, rendering the car somewhat pointless.

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How to Automate the Generation of Training Data for Conversational Bots

Bitext

Everything looks promising in the world of bots: big players are pushing platforms to build them (Google, Amazon, Facebook, Microsoft, IBM, Apple), large retail companies are adopting them (Starbucks, Domino’s, British Airways), press is excited about movies becoming reality; and we users are eager to use. However, one dark hole remains in this scenario.

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Challenges and Opportunities in NLP Benchmarking

Sebastian Ruder

Over the last years, models in NLP have become much more powerful, driven by advances in transfer learning. A consequence of this drastic increase in performance is that existing benchmarks have been left behind. Recent models "have outpaced the benchmarks to test for them" ( AI Index Report 2021 ), quickly reaching super-human performance on standard benchmarks such as SuperGLUE and SQuAD.

NLP 52
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Usage-Based Monetization Musts: A Roadmap for Sustainable Revenue Growth

Speaker: David Warren and Kevin O’Neill Stoll

Transitioning to a usage-based business model offers powerful growth opportunities but comes with unique challenges. How do you validate strategies, reduce risks, and ensure alignment with customer value? Join us for a deep dive into designing effective pilots that test the waters and drive success in usage-based revenue. Discover how to develop a pilot that captures real customer feedback, aligns internal teams with usage metrics, and rethinks sales incentives to prioritize lasting customer eng

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Gradient Descent: Design Your First Machine Learning Model

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Building a simple Machine Learning model using Pytorch from scratch. Image by my great learning Introduction Gradient descent is an optimization algorithm that is used to train machine learning models and is now used in a neural network. Training data helps the model learn […].

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Beginners guide to k-Means Clustering

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Clustering The very first clustering algorithm that most people get exposed to is k-Means clustering. This is probably because it is very simple to understand, however, it has several disadvantages which I will mention later. Clustering is generally viewed as an unsupervised […].

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Granger Causality in Time Series – Explained using Chicken and Egg problem

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction The purpose of this article is to understand what is granger. The post Granger Causality in Time Series – Explained using Chicken and Egg problem appeared first on Analytics Vidhya.

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Caching in Python: the LRU algorithm

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Introduction To use LRU caching in Python, you just need to add two lines – import and declaration of the @lru_cache decorator. We show with examples how and why to use it. Caching is one approach that, if used correctly, significantly speeds up work […]. The post Caching in Python: the LRU algorithm appeared first on Analytics Vidhya.

Algorithm 367
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Churn Prediction- Commercial use of Data Science

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Introduction Churn prediction is probably one of the most important applications of data science in the commercial sector. The thing which makes it popular is that its effects are more tangible to comprehend and it plays a major factor in the overall profits earned […]. The post Churn Prediction- Commercial use of Data Science appeared first on Analytics Vidhya.

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15 Modern Use Cases for Enterprise Business Intelligence

Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?

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Create Stock Exchange Dashboard using Dash in Python!

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Introduction Dash is an open-source web framework for creating analytical dashboards and data visualizations. It helps data analysts to deploy dashboards and serve these dashboards to the main web application. Dash constitutes of three technologies: 1. Plotly.js- It is used for creating beautiful charts […].

Python 348
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Sharpening An Image using OpenCV Library in Python

Analytics Vidhya

This article was published as a part of the Data Science Blogathon From our previous article, we have learned about how to blur an image using a kernel, and we have also learned exactly what a kernel is- It simply refers to the matrix involved in the image manipulation process. For the task of blurring an […]. The post Sharpening An Image using OpenCV Library in Python appeared first on Analytics Vidhya.

Python 343
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Understanding Gradient Descent Algorithm and the Maths Behind It

Analytics Vidhya

This article was published as a part of the Data Science Blogathon This article throws light on how the Gradient Descent algorithm’s core formula is derived which will further help in better understanding of the Gradient Descent Algorithm. First, we will understand what is Gradient Descent algorithm is in brief. A Brief idea of Gradient Descent Algorithm […].

Algorithm 343
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Tensorflow- An impressive deep learning library!

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Introduction Tensorflow (hereinafter – TF) is a fairly young framework for deep machine learning, being developed in Google Brain. For a long time, the framework was developed in a closed mode called disbelief, but after a global refactoring on November 9, 2015, it was […].

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From Diagnosis to Delivery: How AI is Revolutionizing the Patient Experience

Speaker: Simran Kaur, Founder & CEO at Tattva Health Inc.

The healthcare landscape is being revolutionized by AI and cutting-edge digital technologies, reshaping how patients receive care and interact with providers. In this webinar led by Simran Kaur, we will explore how AI-driven solutions are enhancing patient communication, improving care quality, and empowering preventive and predictive medicine. You'll also learn how AI is streamlining healthcare processes, helping providers offer more efficient, personalized care and enabling faster, data-driven

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How nested functions are used in Python?

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Introduction Let’s look at examples of the benefits of nested Python functions and how to use them to encapsulate code, closures, and decorators. Nested (or inner, nested) functions are functions that we define inside other functions to directly access the variables and names defined in […].

Python 337
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Text Preprocessing techniques for Performing Sentiment Analysis!

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Overview In today’s world, one of the biggest sources of information is text data, which is unstructured in nature. Finding customer sentiments from product reviews or feedbacks, extracting opinions from social media data are a few examples of text analytics. Finding insights from text […].

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What are Functions in Python? How to create functions in Python?

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Source Overview: This article aims at brushing up knowledge on the Functions concept in Python in detail. Table of Contents: What are Functions? Types of Functions Built-in User-defined Defining a Function Print vs Return statements Calling a Function Types of Arguments Required arguments Optional […].

Python 306
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Functools -The Power of Higher-Order Functions in Python

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Introduction The Python Standard Library has many great modules to help in keeping your code cleaner and simpler and functools is definitely one of them. The function that accepts a function as an argument and returns a function to the calling function is called […]. The post Functools -The Power of Higher-Order Functions in Python appeared first on Analytics Vidhya.

Python 306
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Prepare Now: 2025s Must-Know Trends For Product And Data Leaders

Speaker: Jay Allardyce, Deepak Vittal, and Terrence Sheflin

As we look ahead to 2025, business intelligence and data analytics are set to play pivotal roles in shaping success. Organizations are already starting to face a host of transformative trends as the year comes to a close, including the integration of AI in data analytics, an increased emphasis on real-time data insights, and the growing importance of user experience in BI solutions.

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Understand The Internal Working of Apache Spark

Analytics Vidhya

This article was published as a part of the Data Science Blogathon In this fast-paced digitized world, the size of data generation is increasing every second. This data cannot be thrown away as this may help to get important business insights. Apache Spark is the largest open-source project for data processing. In this article, I am […]. The post Understand The Internal Working of Apache Spark appeared first on Analytics Vidhya.

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Debugging with IDLE: Find and Fix Bugs In Your Python Code

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Introduction Everyone makes mistakes – even seasoned professional developers, and Python and IDLE are great at catching them. Let’s see how it works. Identifying errors is called debugging, and a debugger is a tool that helps to understand the cause of their occurrence. The […].

Python 314
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Train Your Own YoloV5 Object Detection Model

Analytics Vidhya

This article was published as a part of the Data Science Blogathon “You can have data without information but you cannot have information without data” – Daniel Keys Moran Introduction If you are here then you might be already interested in Machine Learning or Deep Learning so I need not explain what it is? So starting […]. The post Train Your Own YoloV5 Object Detection Model appeared first on Analytics Vidhya.

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Python and MySQL: A Practical Introduction for Data Analysis

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Introduction Let’s look at a practical example of how to make SQL queries to a MySQL server from Python code: CREATE, SELECT, UPDATE, JOIN, etc. Most applications interact with data in some form. Therefore, programming languages ??(Python is no exception) provide tools for storing […].

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The Tumultuous IT Landscape Is Making Hiring More Difficult

After a year of sporadic hiring and uncertain investment areas, tech leaders are scrambling to figure out what’s next. This whitepaper reveals how tech leaders are hiring and investing for the future. Download today to learn more!

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Best Practices and Performance Tuning Activities for PySpark

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Recently I worked on a sas migration project where we converted all the SAS batch jobs to pySpark and deployed them on EMR. In the initial development phase, we used to get few environmental errors which took lots of time to debug and get […]. The post Best Practices and Performance Tuning Activities for PySpark appeared first on Analytics Vidhya.

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Speech Separation by Facebook AI Research

Analytics Vidhya

Objective Understand what is speech separation and why we need it. Discuss the traditional methods of speech separation. Table of contents What is speech separation? Why do we need speech separation? A Brief History of Traditional methods Voice Separation with an Unknown Number of Multiple Speakers Note: All audio samples and the videos, images in […].

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Announcing Machine Learning Certification Course for Beginners!

Analytics Vidhya

Time to Start your Machine Learning Journey for FREE! From face unlock to giving biometric attendance, machine learning seeped into human lives at almost every stage. Machine learning is so extensive that you probably use it numerous times a day involuntarily and unknowingly Currently, Machine Learning is like that golden dream, which everyone wants but […].

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Developing A Course Recommender System using Python

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Introduction Recommender System is a software system that provides specific suggestions to users according to their preferences. These techniques may provide decision-making capabilities to the user. Items refer to any product that the recommender system suggests to its user like movies, music, news, travel […].

Python 291
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Improving the Accuracy of Generative AI Systems: A Structured Approach

Speaker: Anindo Banerjea, CTO at Civio & Tony Karrer, CTO at Aggregage

When developing a Gen AI application, one of the most significant challenges is improving accuracy. This can be especially difficult when working with a large data corpus, and as the complexity of the task increases. The number of use cases/corner cases that the system is expected to handle essentially explodes. 💥 Anindo Banerjea is here to showcase his significant experience building AI/ML SaaS applications as he walks us through the current problems his company, Civio, is solving.

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Python Tutorial: Object-Oriented Programming system (OOPs) – Part 1

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Source In this article, we will try to help you understand/brush up on the basic OOP concepts. Table of Contents: OOP and its importance Class, Instance/Object, __init__ method Creating Classes and Objects Accessing Attributes and Calling methods Variable Types Method Types OOP and its […].

Python 291
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A Technical Approach to Understanding Brain-Computer Interfaces using MNE Python Module

Analytics Vidhya

This article was published as a part of the Data Science Blogathon The intersection of medicine and data science has always been relevant; perhaps the most obvious example is the implementation of neural networks in deep learning. As data science and machine learning advance, so will medicine, but the opposite is also true. Nanotechnology, stem cells, […].

Python 291
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Python Tutorial: Object-Oriented Programming system (OOPs) – Part 2

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Source Overview: In my previous article on OOP, we discussed basic concepts like classes, objects, methods, etc. In this article, we are going to see the main concepts of OOP. They are: Inheritance Single-level Inheritance Multi-level Inheritance Multiple Inheritance Polymorphism Method Overriding […].

Python 271