Analytics Vidhya

AUGUST 25, 2021

This article was published as a part of the Data Science Blogathon Introduction Do you wish you could perform this function using Pandas. Well, there is a good possibility you can! For data scientists who use Python as their primary programming language, the Pandas package is a must-have data analysis tool. The Pandas package has everything […].

Machine Learning 400

Machine Learning Data Scientist Data Analysis Python 400

Dlabs.ai

AUGUST 24, 2021

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.

Robotics 52

Robotics AI AI Algorithm 52

Bitext

AUGUST 24, 2021

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.

Automation 52

Automation Chatbots NLP Machine Learning 52

Sebastian Ruder

AUGUST 23, 2021

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

NLP Natural Language Processing ML Deep Learning 52

Speaker: John Mansour

If you're looking to advance your career in product management, there are more options than just climbing the management ladder. Join our upcoming webinar to learn about highly rewarding career paths that don't involve management responsibilities. We'll cover both career tracks and provide tips on how to position yourself for success in the one that's right for you.

Analytics Vidhya

AUGUST 23, 2021

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 […].

Machine Learning 400

Machine Learning Neural Network Data Science Algorithm 400

Analytics Vidhya

AUGUST 23, 2021

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 […].

Data Science 371

Data Science Algorithm Python Machine Learning 371

Analytics Vidhya

AUGUST 22, 2021

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.

Explainability 368

Explainability Data Science Algorithm Python 368

Analytics Vidhya

AUGUST 24, 2021

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 361

Algorithm Python Data Science 361

Analytics Vidhya

AUGUST 24, 2021

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.

Data Science 353

Data Science Python Machine Learning 353

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Generative AI

Analytics Vidhya

AUGUST 27, 2021

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 337

Python Data Science 337

Analytics Vidhya

AUGUST 26, 2021

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 331

Python Data Science Computer Vision 331

Analytics Vidhya

AUGUST 26, 2021

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 331

Algorithm Data Science ML Python 331

Analytics Vidhya

AUGUST 26, 2021

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 […].

Deep Learning 323

Deep Learning Data Science Machine Learning Python 323

Speaker: Aarushi Kansal, AI Leader & Author and Tony Karrer, Founder & CTO at Aggregage

Software leaders who are building applications based on Large Language Models (LLMs) often find it a challenge to achieve reliability. It’s no surprise given the non-deterministic nature of LLMs. To effectively create reliable LLM-based (often with RAG) applications, extensive testing and evaluation processes are crucial. This often ends up involving meticulous adjustments to prompts.

LLM

Analytics Vidhya

AUGUST 24, 2021

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 323

Python Data Science 323

Analytics Vidhya

AUGUST 27, 2021

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 […].

Text Analytics 315

Text Analytics Data Science NLP Python 315

Analytics Vidhya

AUGUST 26, 2021

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 306

Python Data Science 306

Analytics Vidhya

AUGUST 26, 2021

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.

Deep Learning 306

Deep Learning Explainability Machine Learning Data Science 306

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Analytics Vidhya

AUGUST 26, 2021

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 296

Python Data Science 296

Analytics Vidhya

AUGUST 26, 2021

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.

Data Science 296

Data Science Python 296

Analytics Vidhya

AUGUST 25, 2021

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 296

Python Data Science 296

Analytics Vidhya

AUGUST 26, 2021

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.

Data Science 284

Data Science Python 284

Speaker: Scott Sehlhorst

We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.

Analytics Vidhya

AUGUST 26, 2021

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 284

Python Neural Network Deep Learning Data Science 284

Analytics Vidhya

AUGUST 25, 2021

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 […].

Machine Learning 284

Machine Learning 284

Analytics Vidhya

AUGUST 25, 2021

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 […].

Data Analysis 284

Data Analysis Python Data Science 284

Analytics Vidhya

AUGUST 25, 2021

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 284

Python Data Science Machine Learning 284

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Data Analysis

Analytics Vidhya

AUGUST 24, 2021

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 284

Python Data Science 284

Analytics Vidhya

AUGUST 24, 2021

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 […].

AI Researcher 284

AI Researcher AI Research AI AI 284

Analytics Vidhya

AUGUST 25, 2021

This article was published as a part of the Data Science Blogathon Introduction In this article, we’ll look at a different approach to K Means clustering called Hierarchical Clustering. In comparison to K Means or K Mode, hierarchical Clustering has a different underlying algorithm for how the clustering mechanism works. Hierarchical clustering uses agglomerative or divisive […].

Algorithm 283

Algorithm Python Data Science Machine Learning 283