Analytics Vidhya

NOVEMBER 12, 2021

This article was published as a part of the Data Science Blogathon This article starts by discussing the fundamentals of Natural Language Processing (NLP) and later demonstrates using Automated Machine Learning (AutoML) to build models to predict the sentiment of text data. Other applications of NLP are for translation, speech recognition, chatbot, etc.

Natural Language Processing 400

Natural Language Processing Machine Learning Automation NLP 400

Eugene Yan

NOVEMBER 6, 2021

Susan shares 5 lessons she gained from writing online in public over the past year.

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100

James Thorn

NOVEMBER 7, 2021

Learn how to contribute to the Parchain auction of the Acala team and the possible ROI of the Investment Continue reading on Medium »

Explainability 52

Explainability 52

DeepMind

NOVEMBER 8, 2021

Our brain has an amazing ability to process visual information. We can take one glance at a complex scene, and within milliseconds be able to parse it into objects and their attributes, like colour or size, and use this information to describe the scene in simple language. Underlying this seemingly effortless ability is a complex computation performed by our visual cortex, which involves taking millions of neural impulses transmitted from the retina and transforming them into a more meaningful f

Deep Learning 57

Deep Learning 57

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

NOVEMBER 9, 2021

This article was published as a part of the Data Science Blogathon In this article, I am going to build multiple neural network models to solve a regression problem. Before we start working on the model, I would like to give a brief overview of what we will touch on and what steps we will follow. […]. The post Neural Network for Regression with Tensorflow appeared first on Analytics Vidhya.

Neural Network 398

Neural Network Data Science Deep Learning Python 398

Analytics Vidhya

NOVEMBER 10, 2021

This article was published as a part of the Data Science Blogathon Image Source: Author Introduction to Fitness Tracker Market With the advancements in the IT domain, wearable devices have been in great demand in the recent past. A wearable device is simply a device that can be worn by the user and this device is […]. The post How To Use Python To Analyse Fitness Tracker Market: Step By Step EDA appeared first on Analytics Vidhya.

Python 388

Python Data Science 388

Analytics Vidhya

NOVEMBER 12, 2021

This article was published as a part of the Data Science Blogathon Introduction Hey all, I am sure you must have played pokemon games at some point in time and must have hated the issue of creating an optimal and balanced team to gain an advantage. What if I say one can do this by having […]. The post Optimizing Pokemon Team using Python’s PuLP Library appeared first on Analytics Vidhya.

Python 382

Python Data Science Machine Learning 382

Analytics Vidhya

NOVEMBER 8, 2021

This article was published as a part of the Data Science Blogathon. Getting Started With… Natural Language Processing (NLP) is the field of artificial intelligence that relates lingual to Computer Science. I am assuming that you have understood the basic concepts of NLP. So we will move ahead. There are Some NLP applications as follows: […].

NLP 380

NLP Python Natural Language Processing Artificial Intelligence 380

Analytics Vidhya

NOVEMBER 6, 2021

This article was published as a part of the Data Science Blogathon. Table of contents Introduction What is Microsoft Power BI? Microsoft Power BI Concepts Data sources in Microsoft Power BI Import Excel Data to Microsoft Power BI Query Editor Inbuilt visuals Conclusion Introduction There is so much data collected in businesses and industries today. […].

Data Science 357

Data Science 357

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Generative AI is upending the way product developers & end-users alike are interacting with data. Despite the potential of AI, many are left with questions about the future of product development: How will AI impact my business and contribute to its success? What can product managers and developers expect in the future with the widespread adoption of AI?

Generative AI

Analytics Vidhya

NOVEMBER 8, 2021

This article was published as a part of the Data Science Blogathon Overview of Linear Regression “Without understanding the engine, building or working with a car is just playing with metal” This seems to be true in almost all domains of life, without fundamentals; creation and innovation are simply not possible. In this guide, we will […].

Data Science 348

Data Science Deep Learning Python 348

Analytics Vidhya

NOVEMBER 6, 2021

This article was published as a part of the Data Science Blogathon. Introduction In the field of Data Science, the most important thing is to prepare the data or clean the data for further model building, data exploration, or data visualization, etc. For this Pandas is a very powerful library in python because it has […]. The post A Simple Guide to Pandas Dataframe Operations appeared first on Analytics Vidhya.

Data Science 343

Data Science Python 343

Analytics Vidhya

NOVEMBER 9, 2021

This article was published as a part of the Data Science Blogathon Introduction to Regularization During the Machine Learning model building, the Regularization Techniques is an unavoidable and important step to improve the model prediction and reduce errors. This is also called the Shrinkage method. Which we use to add the penalty term to control the complex […].

Machine Learning 337

Machine Learning Data Science Python 337

James Thorn

NOVEMBER 7, 2021

A deep dive into how to participate and an analysis of the top candidates and the possible ROI Continue reading on Medium »

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52

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

DeepMind

NOVEMBER 8, 2021

Our brain has an amazing ability to process visual information. We can take one glance at a complex scene, and within milliseconds be able to parse it into objects and their attributes, like colour or size, and use this information to describe the scene in simple language. Underlying this seemingly effortless ability is a complex computation performed by our visual cortex, which involves taking millions of neural impulses transmitted from the retina and transforming them into a more meaningful f

Deep Learning 57

Deep Learning 57