Sat.Aug 13, 2022 - Fri.Aug 19, 2022

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Building a simple Flask App using Docker vs Code

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction More often than not, developers run into issues of an application running on one machine versus not running on another. Dockers help prevent this by ensuring the application runs on any machine if it works on yours. Simply put, if your job as […]. The post Building a simple Flask App using Docker vs Code appeared first on Analytics Vidhya.

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AI in Supply Chain — A Trillion Dollar Opportunity

DataRobot Blog

Supply chain and logistics industries worldwide lose over $1 trillion a year due to out-of-stock or overstocked items 1. Shifting demands and shipping difficulties make the situation worse. Challenges in inventory management, demand forecasting, price optimization, and more can result in missed opportunities and lost revenue. The retail marketplace has become increasingly complex and competitive.

AI 98
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Simplicity is An Advantage but Sadly Complexity Sells Better

Eugene Yan

Pushing back on the cult of complexity.

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Discovering when an agent is present in a system

DeepMind

We want to build safe, aligned artificial general intelligence (AGI) systems that pursue the intended goals of its designers. Causal influence diagrams (CIDs) are a way to model decision-making situations that allow us to reason about agent incentives. By relating training setups to the incentives that shape agent behaviour, CIDs help illuminate potential risks before training an agent and can inspire better agent designs.

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How To Get Promoted In Product Management

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.

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The DataHour: Your Upcoming Learning Timeline

Analytics Vidhya

Dear Readers, Data Science is a vast subject, and the learning you can get is immense. And we at Analytics Vidhya always try to bring new learning topics and build up your skills. This time, we have not one, not two, but six new DataHour for you to attend. So, keep your notepad handy and […]. The post The DataHour: Your Upcoming Learning Timeline appeared first on Analytics Vidhya.

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Take the Route to AI Success with DataOps and MLOps

DataRobot Blog

If you’ve been keeping up with business literature lately, you know that adopting artificial intelligence (AI) strategies can increase company revenue, improve efficiency, and keep customers happy. But even the best models cannot improve performance until they are put into production. What are companies actually doing today? Alexander Rode and Timm Grosser, analysts at the Business Application Research Center (BARC), decided to find out by surveying 248 companies from a variety of industries abo

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Discovering when an agent is present in a system

DeepMind

We want to build safe, aligned artificial general intelligence (AGI) systems that pursue the intended goals of its designers. Causal influence diagrams (CIDs) are a way to model decision-making situations that allow us to reason about agent incentives. By relating training setups to the incentives that shape agent behaviour, CIDs help illuminate potential risks before training an agent and can inspire better agent designs.

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AWS Glue for Handling Metadata

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction AWS Glue helps Data Engineers to prepare data for other data consumers through the Extract, Transform & Load (ETL) Process. The managed service offers a simple and cost-effective method of categorizing and managing big data in an enterprise. It provides organizations with […].

Metadata 365
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Test your Data Science Skills on Transformers library

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Transformers were one of the game-changer advancements in Natural language processing in the last decade. A team at Google Brain developed Transformers in 2017, and they are now replacing RNN models like long short-term memory(LSTM) as the model of choice for NLP […].

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Navigating the Future: Generative AI, Application Analytics, and Data

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?

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Introduction to Apache Spark and its Datasets

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction In this article, we will introduce you to the big data ecosystem and the role of Apache Spark in Big data. We will also cover the Distributed database system, the backbone of big data. In today’s world, data is the fuel. Almost […]. The post Introduction to Apache Spark and its Datasets appeared first on Analytics Vidhya.

Big Data 291
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Image Contrast Enhancement Using CLAHE

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Contrast enhancement algorithms have evolved over the last few decades to meet the needs of its objectives. There are two main goals in enhancing an image’s contrast: (i) Improving its appearance for visual interpretation and (ii) facilitating/increasing the performance of subsequent tasks […].

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What is Apache Impala- Features and Architecture

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Impala is an open-source and native analytics database for Hadoop. Vendors such as Cloudera, Oracle, MapReduce, and Amazon have shipped Impala. If you want to learn all things Impala, you’ve come to the right place. source: -[link] It rapidly processes large […].

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Basic Introduction to Data Science Pipeline

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction The Data science pipeline is the procedure and equipment used to compile raw data from many sources, evaluate it, and display the findings in a clear and concise manner. Businesses use the method to get answers to certain business queries and produce […]. The post Basic Introduction to Data Science Pipeline appeared first on Analytics Vidhya.

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Peak Performance: Continuous Testing & Evaluation of LLM-Based Applications

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.

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Database Normalization- A Step-by-Step Guide with Examples

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction As an SQL Developer, you regularly work with enormous amounts of data stored in different tables that are present inside databases. This often becomes difficult to extract the information if it is not organized properly. We can solve this problem using Normalization by […].

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Build your Recommendation System using MLIB

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Almost every one of us nowadays is using YouTube, and it turned out to be fascinating to know how YouTube recommends videos in the same genre/type that we watched a day ago, an hour ago, or a minute ago. In the backend, […]. The post Build your Recommendation System using MLIB appeared first on Analytics Vidhya.

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Dealing with outliers using the Z-Score method

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Outlier detection is one of the widely used methods in any data science project, as its presence can lead to the development of a bad machine learning model. Let’s take a quick scenario of the linear regression problem statement, where suppose you […]. The post Dealing with outliers using the Z-Score method appeared first on Analytics Vidhya.

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Colorization of Faded Images

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction In this article, we shall make an ML model in Python that will be able to add colors to old, washed-away, and faded images. In summary, we have to achieve the target of colorizing images using ML. What we are going to […]. The post Colorization of Faded Images appeared first on Analytics Vidhya.

Python 283
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How to Improve Email Deliverability and Optimize Each Send

Learn how to optimize email deliverability and drive greater email ROI. What lands your email in the customer’s inbox? Understanding those factors, otherwise known as email deliverability, is critical to getting the most return on your campaign investments. But the “rules” around which factors land you in the spam folder aren’t always easy to keep up with.

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Getting Started with RESTful APIs and Fast API

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction In this article, we will explore the details of RESTful architecture, the merits of Fast API, and how to create a simple API with Fast API. But before that, we shall discuss some basics of APIs like their functionalities, uses, and architectures, […]. The post Getting Started with RESTful APIs and Fast API appeared first on Analytics Vidhya.

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Building a Content-Based Recommendation System

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Back in 2000, people used to purchase groceries from their local hypermarts. However, in the last 20 years, several online e-commerce stores have been launched. So, instead of going to a physical store, you can visit an online e-commerce store from the […]. The post Building a Content-Based Recommendation System appeared first on Analytics Vidhya.

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Template for Data Cleaning using Python

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Data cleaning is one area in the Data Science life cycle that not even data analysts have to do. Still, data scientists and their daily task are to clean the data so that machine learning algorithms will have the data good enough to […]. The post Template for Data Cleaning using Python appeared first on Analytics Vidhya.

Python 271
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Step-by-step Explanation of Text Classification

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Suppose you are working in an IT firm as a support desk specialist and receive hundreds of support tickets you have to handle daily. The first task you do with each ticket is to classify it into one of the categories you […]. The post Step-by-step Explanation of Text Classification appeared first on Analytics Vidhya.

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Understanding User Needs and Satisfying Them

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.

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Different Ways of Loading Data using Python

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction When we started our data science journey the very first library that got our way was pandas and the very first function was read_csv(). But do we have only a CSV file to read? No right! This article will let you know […]. The post Different Ways of Loading Data using Python appeared first on Analytics Vidhya.

Python 265
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On-Device Personalization of ASR Models for Disordered Speech

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Speech impairments afflict millions of people with underlying reasons, including neurological or hereditary diseases, physical handicaps, brain damage, hearing loss, etc. Furthermore, the resulting speech patterns are diverse and complex, including stuttering, dysarthria, apraxia, etc., and adding to that; there is a […].

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Introduction to Spark Streaming

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction We, as a learner, are in the stage of analyzing the data mostly in the CSV format. Still, we need to understand that at the enterprise level, most of the work is done in real-time, where we need skills to stream live data. […]. The post Introduction to Spark Streaming appeared first on Analytics Vidhya.