Sat.Feb 05, 2022 - Fri.Feb 11, 2022

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Managing Your Reusable Python Code as a Data Scientist

KDnuggets

Here are a few approaches that I have settled on for managing my own reusable Python code as a data scientist, presented from most to least general code use, and aimed at beginners.

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Different Types of Cross-Validations in Machine Learning

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Model Development is a critical stage in the life cycle of a Data Science project. We attempt to train our data set using various forms of Machine Learning models, either supervised or unsupervised, depending on the Business Problem. Given many models available for […].

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Deepdub closes fresh round for dubbing AI that dubs movies, shows, and games

Dataconomy

Dubbing, where recordings in other languages are lip-synced and mixed with a show’s original soundtrack, is an exploding business. One localization platform, Zoo Digital, saw revenues jump by 73% to $28.6 million in July 2018 compared to the year prior. Another, BTI Studios, told Television Business International that dubbing grew from 3%.

AI 240
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Stop paying for APIs to calculate distances and use this Open Source tool!

Applied Data Science

How to use OSRM to calculate distances reliably and for free. Photo by T.H. Chia on Unsplash Calculating distances between a set of coordinates is something that regularly comes up in Data Science projects. Whether it is planning routes for delivery services, or measuring a customer’s willingness to travel to certain locations, getting an accurate measure of distance is always key.

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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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The Complete Collection of Data Science Cheat Sheets – Part 1

KDnuggets

A collection of cheat sheets that will help you prepare for a technical interview, assessment tests, class presentation, and help you revise core data science concepts.

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Optimal Resource Allocation using Python

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Objective “True optimization is the revolutionary contribution of modern research to decision processes” – George Dantzig. This article discusses solving a resource allocation problem using linear programming in Python. We will find an optimal value for a linear equation with different linear constraints.

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More Trending

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Age of Moms When Kids are Born

FlowingData

People have kids at a wide range of ages, but the moments tend towards where we are in life. There are social norms and biological norms. Based on data from the National Center for Health Statistics, we can see how these ranges shift by child number. Read More.

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How to Learn Math for Machine Learning

KDnuggets

So how much math do you need to know in order to work in the data science industry? The answer: Not as much as you think.

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11 Extensions to Power Up your Jupyter Notebook

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. […]. The post 11 Extensions to Power Up your Jupyter Notebook appeared first on Analytics Vidhya.

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DirectX Visualization Optimizes Analytics Algorithmic Traders

Smart Data Collective

Learn how DirectX visualization can improve your study and assessment of different trading instruments for maximum productivity and profitability. Analytics technology has become an invaluable aspect of modern financial trading. A growing number of traders are using increasingly sophisticated data mining and machine learning tools to develop a competitive edge.

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Get Better Network Graphs & Save Analysts Time

Many organizations today are unlocking the power of their data by using graph databases to feed downstream analytics, enahance visualizations, and more. Yet, when different graph nodes represent the same entity, graphs get messy. Watch this essential video with Senzing CEO Jeff Jonas on how adding entity resolution to a graph database condenses network graphs to improve analytics and save your analysts time.

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Bubble tea combinations, a visual breakdown

FlowingData

Walk into a boba shop and usually you’ll see a large menu that lists the options for your tea, milk, toppings, ice, and sweetness. With all the variations, you get a lot of combinations. Julia Janicki and Daisy Chung broke it down with an interactive that takes you through the steps. Tags: boba , combinations , Daisy Chung , Julia Janicki.

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Junior Data Scientist: The Next Level

KDnuggets

There is a difference in the level of experience compared to Junior, Mid-Level, and Senior Data Scientists. This article will go through the expectations for all job roles and what is required to move up the ladder.

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Workflow of MLOps: Part 2 | Model Building

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. This is the 2nd blog of the MLOps series. Introduction This article is part of an ongoing blog series on Machine Learning Operations(MLOps). In the previous article, we have gone through the introduction of MLOps. We have seen differences in traditional software development in […].

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Cloud Technology Makes Virtual Assistants More Beneficial than Ever

Smart Data Collective

More companies are relying on cloud technology than ever before. They are discovering the benefits of using the cloud to utilize data and facilitate communications between employees, customers, contractors and other stakeholders. One of the underappreciated benefits of cloud technology is that it makes it easier to work with virtual assistants. Savvy executives and small business owners realize that virtual assistants can perform many important tasks a lot more efficiently.

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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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? Good Redundant – The Process 176

FlowingData

Welcome to issue #176 of The Process , the newsletter for FlowingData members about how the charts get made. I’m Nathan Yau, and this week I’m thinking about using more color, and more generally, using more encodings to show the same thing in one chart. Become a member for access to this — plus tutorials, courses, and guides.

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The Not-so-Sexy SQL Concepts to Make You Stand Out

KDnuggets

Databases are the houses of our data and data scientists HAVE TO HAVE A KEY! In this article, I discuss some lesser known concepts of SQL that data scientists do not familiarize themselves with.

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Exploratory Data Analysis in Python

Analytics Vidhya

Overview Understanding how EDA is done in Python Various steps involved in the Exploratory Data Analysis Performing EDA on a given dataset Introduction Exploratory data analysis popularly known as EDA is a process of performing some initial investigations on the dataset to discover the structure and the content of the given dataset. It is often […].

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5 Data Security Strategies Businesses Should Implement

Smart Data Collective

We have witnessed some horrifying data breaches over the last year. One of the worst was when a team of Chinese hackers penetrated the security of the Microsoft Exchange and accessed the accounts of over 250,000 global organizations. The Colonial Pipeline and SolarWinds were also victims to hackers. While large corporations like these will continue to be targets for data breaches, small businesses are also at risk.

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Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You Need to Know

Speaker: Timothy Chan, PhD., Head of Data Science

Are you ready to move beyond the basics and take a deep dive into the cutting-edge techniques that are reshaping the landscape of experimentation? 🌐 From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.

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How Records of Processing Activities (ROPA) Can Benefit Your Business

Dataversity

GDPR introduced the Records of Processing Activities (ROPA) requirements to drive better accountability from organizations with their use of personal data. Before GDPR, organizations didn’t track how they used and shared personal data, making data privacy risks impossible to comprehend. Now GDPR mandates that organizations create and maintain essential information about how an organization uses personal data. […].

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5 Ways to Apply AI to Small Data Sets

KDnuggets

It is better to use AI algorithms on small data sets for results free of human errors and false results when applied correctly. Here are some methods to apply AI to small data sets.

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Folder Management in Python

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Overview “You’re either the one that creates the automation or you’re getting automated.” Tom Preston-Werner. Automation affects almost every aspect of modern life, and it can be used in any industry. Automation minimizes human input and eliminates doing repetitive tasks.

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Past redlining still seen in the present

FlowingData

In the 1930s, a group called the Home Owners’ Loan Corporation went to cities classifying neighborhoods based on the “risk” of defaulting on loans. Areas deemed highest risk were marked with red ink on a map, and these areas tended to be non-white. The classification, redlining, was made illegal, but you can still see the effects today, as shown by Ryan Best and Elena Mejía with these interactive maps for FiveThirtyEight.

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How Embedded Analytics Gets You to Market Faster with a SAAS Offering

Start-ups & SMBs launching products quickly must bundle dashboards, reports, & self-service analytics into apps. Customers expect rapid value from your product (time-to-value), data security, and access to advanced capabilities. Traditional Business Intelligence (BI) tools can provide valuable data analysis capabilities, but they have a barrier to entry that can stop small and midsize businesses from capitalizing on them.

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Why AI Is Important for Automating Travel Policy Compliance

Smart Data Collective

Artificial intelligence (AI) is a trending topic commonly spoken about globally. It has come to a point where all the repetitive work that we have to do manually is taken care of by the AI. 37% of businesses and organizations employ AI, and about 15% claim to use its capabilities. So, the real question is how can AI help businesses in travel? Well, as far as many businesses are concerned, AI has many advanced capabilities in managing expenses, optimizing travel programs, and improving the overal

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Build a Web Scraper with Python in 5 Minutes

KDnuggets

In this article, I will show you how to create a web scraper from scratch in Python.

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Heart Disease Prediction using Machine Learning

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Overview In this article, we will be closely working with the heart disease prediction and for that, we will be looking into the heart disease dataset from that dataset we will derive various insights that help us know the weightage of each feature and […]. The post Heart Disease Prediction using Machine Learning appeared first on Analytics Vidhya.

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Frequency trails in the snow

FlowingData

Same vibes pic.twitter.com/oXjhdwS3yW. — Matt Blackwell (@matt_blackwell) February 7, 2022. This is a good tweet. Tags: humor , snow.

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Manufacturing Sustainability Surge: Your Guide to Data-Driven Energy Optimization & Decarbonization

Speaker: Kevin Kai Wong, President of Emergent Energy Solutions

In today's industrial landscape, the pursuit of sustainable energy optimization and decarbonization has become paramount. Manufacturing corporations across the U.S. are facing the urgent need to align with decarbonization goals while enhancing efficiency and productivity. Unfortunately, the lack of comprehensive energy data poses a significant challenge for manufacturing managers striving to meet their targets.

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IP Scores Are Crucial to the Future of Data Security in 2022

Smart Data Collective

Have you stopped to think about the state of the Internet and the role it plays in our daily lives? We are more connected today than ever before. The Internet has unquestionably brought a lot of benefits to our lives. However, it has also created a lot of risks. As more data is stored over the Internet, we are more vulnerable than ever. In the first six months of 2019, over 4.1 billion records were exposed in data breaches.

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KDnuggets™ News 22:n06, Feb 9: Data Science Programming Languages and When To Use Them; Complete Collection of Data Science Cheat Sheets

KDnuggets

Data Science Programming Languages and When To Use Them; The Complete Collection of Data Science Cheat Sheets – Part 1; Build a Web Scraper with Python in 5 Minutes; 8 Best Data Science Courses to Enroll in 2022 For Steep Career Advancement; Classifying Long Text Documents Using BERT.

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Guide On Customer Churn: Don’t Just Predict, Prevent it!

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Phonepe, Google Pay (Tez) are ubiquitous names in the Indian payment ecosystem and the top two players in the area. According to Phonepe pulse report, it has133 million monthly active users as of July’21. For the Q3-21 quarter, the total transactions were 526.8 Cr […].

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Red Teaming Language Models with Language Models

DeepMind

In our recent paper, we show that it is possible to automatically find inputs that elicit harmful text from language models by generating inputs using language models themselves. Our approach provides one tool for finding harmful model behaviours before users are impacted, though we emphasize that it should be viewed as one component alongside many other techniques that will be needed to find harms and mitigate them once found.

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From Developer Experience to Product Experience: How a Shared Focus Fuels Product Success

Speaker: Anne Steiner and David Laribee

As a concept, Developer Experience (DX) has gained significant attention in the tech industry. It emphasizes engineers’ efficiency and satisfaction during the product development process. As product managers, we need to understand how a good DX can contribute not only to the well-being of our development teams but also to the broader objectives of product success and customer satisfaction.