Sat.Jul 11, 2020 - Fri.Jul 17, 2020

article thumbnail

5 Striking Pandas Tips and Tricks for Analysts and Data Scientists

Analytics Vidhya

Overview Pandas provide tools and techniques to make data analysis easier in Python We’ll discuss tips and tricks that will help you become a. The post 5 Striking Pandas Tips and Tricks for Analysts and Data Scientists appeared first on Analytics Vidhya.

article thumbnail

9 Best Practices Every Data Science Leader Should Follow

Dataconomy

Being a data scientist is hard. In addition to the combination of advanced mathematics and coding skills required to do the job, it’s a newer role for many organizations, so data scientists are called upon to navigate corporate landscapes, source the right IT resources, and establish new workflows across departments. The post 9 Best Practices Every Data Science Leader Should Follow appeared first on Dataconomy.

professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

What I Do During A Data Science Project To Deliver Success

Eugene Yan

It's not enough to have a good strategy and plan. Execution is just as important.

article thumbnail

How to Reduce your GeoJSON File Size Smaller for Better Performance

learn data science

Explains how to reduce the file size of your GeoJSON file using a tool called “mapshaper”. Problem If you use large size GeoJSON files, the map tends to be slow and it may even hang in the worst case. Typically, the map rendering becomes slower if the file size exceeds 20–30M (depending on how the GeoJSON is constructed though). This is the same story when you use GeoJSON map in Exploratory , too.

article thumbnail

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?

article thumbnail

Hypothesis Testing: A Way to Prove Your Claim Using p-value

Analytics Vidhya

Introduction One of the most basic concepts in statistics is hypothesis testing. Not just in Data Science, Hypothesis testing is important in every field. The post Hypothesis Testing: A Way to Prove Your Claim Using p-value appeared first on Analytics Vidhya.

article thumbnail

How to form a close-knit data science team in weeks

Dataconomy

David Kuntz, Head of Data Science at Degreed, discusses how to find and form a close-knit, full-stack data science team in weeks. We’ve all heard about data science unicorns – people with an almost mythical set of skills that can bring real clout and power into your organisation. But searching. The post How to form a close-knit data science team in weeks appeared first on Dataconomy.

More Trending

article thumbnail

Getting the Most From a Podcast – An interview with Fiyin Obayan

Data Science 101

The post Getting the Most From a Podcast – An interview with Fiyin Obayan appeared first on Ryan Swanstrom.

52
article thumbnail

KNNImputer: A robust way to impute missing values (using Scikit-Learn)

Analytics Vidhya

Overview Learn to use KNNimputer to impute missing values in data Understand the missing value and its types Introduction KNNImputer by scikit-learn is a. The post KNNImputer: A robust way to impute missing values (using Scikit-Learn) appeared first on Analytics Vidhya.

Analytics 351
article thumbnail

A/B test your tech stack

Twilio Segment

Learn how to design, run, and analyze an A/B test to determine what marketing tools are generating the most ROI.

40
article thumbnail

Alation Named Leader in IDC’s Inaugural Data Catalog Assessment

Alation

The post Alation Named Leader in IDC’s Inaugural Data Catalog Assessment appeared first on Alation.

52
article thumbnail

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.

article thumbnail

Top 20 Visualization Dashboards for Mapping COVID-19

Analytics Vidhya

Introduction The best way to track the COVID-19 outbreak is by using data and visualization. The COVID-19 patterns are sometimes contradictory and this is. The post Top 20 Visualization Dashboards for Mapping COVID-19 appeared first on Analytics Vidhya.

Analytics 342
article thumbnail

Difference between SQL Keys (Primary Key, Super Key, Candidate Key, Foreign Key)

Analytics Vidhya

Introduction SQL Keys is the Key to your success in Analytics! Data is growing at an exponential rate and so is the demand for. The post Difference between SQL Keys (Primary Key, Super Key, Candidate Key, Foreign Key) appeared first on Analytics Vidhya.

SQL 343
article thumbnail

8 Business Analytics Books to Begin Your Journey

Analytics Vidhya

Introduction The global spread of the internet has made the availability of knowledge easy. Every information is at the grasp of our palms. As. The post 8 Business Analytics Books to Begin Your Journey appeared first on Analytics Vidhya.

Analytics 299
article thumbnail

Limitations of AUC-ROC technique

Analytics Vidhya

Overview As I had promised in my previous article, now, it’s time to complete our discussion on evaluation metrics for classification problems. Today, we. The post Limitations of AUC-ROC technique appeared first on Analytics Vidhya.

Analytics 171
article thumbnail

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.