- The Easiest Way to Make Beautiful Interactive Visualizations With Pandas - Dec 28, 2021.
Check out these one-liner interactive visualization with Pandas in Python.
- How to Create an Interactive Dashboard in Three Steps with KNIME Analytics Platform - Oct 19, 2021.
In this blog post I will show you how to build a simple, but useful and good-looking dashboard to present your data - in three simple steps!
- Step by Step Building a Vacancy Tracker Using Tableau - Oct 12, 2021.
Step-by-step explanations of vacancies valued in tens of millions of dollars in the small town of Fitchburg, Massachusetts.
- Path to Full Stack Data Science - Sep 27, 2021.
Start your journey toward mastering all aspects of the field of Data Science with this focused list of in-depth self-learning resources. Curated with the beginner in mind, these recommendations will help you learn efficiently, and can also offer existing professionals useful highlights for review or help filling in any gaps in skills.
- Real-Time Histogram Plots on Unbounded Data - Sep 24, 2021.
Using histograms on real-time data is not possible in most of the popular data science libraries. In this article you will learn how dynamically compute and display a histogram within a Python notebook.
- 5 Must Try Awesome Python Data Visualization Libraries - Sep 15, 2021.
The goal of data visualization is to communicate data or information clearly and effectively to readers. Here are 5 must try awesome Python libraries for helping you do so, with overviews and links to quick start guides for each.
- Speeding up data understanding by interactive exploration - Aug 19, 2021.
A key success factor of data science projects is to understand the data well. This blog explains why coding can be inefficient for this and how you can improve.
- Querying the Most Granular Demographics Dataset - Aug 13, 2021.
Having access to broad and detailed population data can potentially offer enormous value to any organization looking to interact with specific demographics. However, access alone is not sufficient without being able to leverage advanced techniques to explore and visualize the data.
- How Visualization is Transforming Exploratory Data Analysis - Aug 4, 2021.
Data analysts are dealing with bigger datasets than ever before, making interrogation difficult. Visualized Exploratory Data Analysis, supported by advanced parallel computing, promises an answer.
- AWS Webinar: How are data-driven companies using ESG and sustainability data to make actionable decisions? - Jul 15, 2021.
In this virtual session, on Jul 29 @ 11AM PT, 2PM ET, our panel of experts will uncover how companies across several verticals use ESG data to move beyond the reporting benchmark, deepen business insights, and create competitive differentiation.
- A Lightning Fast Look at Single Line Exploratory Data Analysis - Jul 8, 2021.
Here's a very quick look at how you can perform EDA with a single line of code using D-Tale.
- ROC Curve Explained - Jul 6, 2021.
Learn to visualise a ROC curve in Python.
- How to create an interactive 3D chart and share it easily with anyone - Jun 25, 2021.
This is a short tutorial on a great Plotly feature.
- Data storytelling: brains are built for visuals, but hearts turn on stories - Jun 17, 2021.
Today, we need much more than just numbers about our organization to understand, gain insights, and take relevant actions. While visualizations of the data are important, making an emotional connection with the stories behind the data is key. If you want to sell a story, send a missile to the heart.
- Get Interactive Plots Directly With Pandas - Jun 14, 2021.
Telling a story with data is a core function for any Data Scientist, and creating data visualizations that are simultaneously illuminating and appealing can be challenging. This tutorial reviews how to create Plotly and Bokeh plots directly through Pandas plotting syntax, which will help you convert static visualizations into interactive counterparts -- and take your analysis to the next level.
- How to Generate Automated PDF Documents with Python - Jun 10, 2021.
Discover how to leverage automation to create dazzling PDF documents effortlessly.
- SAS® Visual Data Science Decisioning powered by SAS® Viya®: Free Trial - Jun 8, 2021.
SAS® Visual Data Science Decisioning provides the ultimate analytics experience. Start your free trial and get access to the latest in data visualization, machine learning, forecasting, model deployment and more.
- This Data Visualization is the First Step for Effective Feature Selection - Jun 8, 2021.
Understanding the most important features to use is crucial for developing a model that performs well. Knowing which features to consider requires experimentation, and proper visualization of your data can help clarify your initial selections. The scatter pairplot is a great place to start.
- Animated Bar Chart Races in Python - May 18, 2021.
A quick and step-by-step beginners project to create an animation bar graph for an amazing Covid dataset.
- Essential Linear Algebra for Data Science and Machine Learning - May 10, 2021.
Linear algebra is foundational in data science and machine learning. Beginners starting out along their learning journey in data science--as well as established practitioners--must develop a strong familiarity with the essential concepts in linear algebra.
- KDnuggets™ News 21:n17, May 5: Charticulator: Microsoft Research open-source game-changing Data Visualization platform; Data Science to Predict and Prevent Real World Problems - May 5, 2021.
Charticulator: Microsoft Research game-changing Data Visualization platform; How Data Science is used to predict and prevent real world problems; Hilarious Data Science Humor; Neural Networks for Natural Language Processing Now; and more.
- A simple static visualization can often be the best approach - May 4, 2021.
How I overengineered a worse solution by making an interactive visualization.
- Charticulator: Microsoft Research open-sourced a game-changing Data Visualization platform - May 3, 2021.
Creating grand charts and graphs from your data analysis is supported by many powerful tools. However, how to make these visualizations meaningful can remain a mystery. To address this challenge, Microsoft Research has quietly open-sourced a game-changing visualization platform.
- How to Make Sure Your Analysis Actually Gets Used - Apr 7, 2021.
Few things are as demoralizing as seeing your data analysis tossed aside. Learn from these tips -- assembled from experience, academic research, and industry best practice -- on how to make sure your hard work receives the credit it deserves and delivers the value to your organization that you expect.
- How to break a model in 20 days — a tutorial on production model analytics - Mar 29, 2021.
This is an article on how models fail in production, and how to spot it.
- Data Science Curriculum for Professionals - Mar 25, 2021.
If you are looking to expand or transition your current professional career that is buried in spreadsheet analysis into one powered by data science, then you are in for an exciting but complex journey with much to explore and master. To begin your adventure, following this complete road map to guide you from a gnome in the forest of spreadsheets to an AI wizard known far and wide throughout the kingdom.
- Solve for Success: The Transformative Power of Data Visualization - Mar 24, 2021.
Learn from experts and hear real-world use cases about how you and your organization can optimize data to enable innovation through visualization. Register now.
- How to frame the right questions to be answered using data - Mar 18, 2021.
Understanding your data first is a key step before going too far into any data science project. But, you can't fully understand your data until you know the right questions to ask of it.
- KDnuggets™ News 21:n11, Mar 17: Is Data Scientist still a satisfying job? How To Overcome The Fear of Math and Learn Math For Data Science - Mar 17, 2021.
Must Know for Data Scientists and Data Analysts: Causal Design Patterns; Know your data much faster with the new Sweetviz Python library; The Inferential Statistics Data Scientists Should Know; Natural Language Processing Pipelines, Explained
- Know your data much faster with the new Sweetviz Python library - Mar 12, 2021.
One of the latest exploratory data analysis libraries is a new open-source Python library called Sweetviz, for just the purposes of finding out data types, missing information, distribution of values, correlations, etc. Find out more about the library and how to use it here.
- Beautiful decision tree visualizations with dtreeviz - Mar 8, 2021.
Improve the old way of plotting the decision trees and never go back!
- 11 Essential Code Blocks for Complete EDA (Exploratory Data Analysis) - Mar 5, 2021.
This article is a practical guide to exploring any data science project and gain valuable insights.
- Powerful Exploratory Data Analysis in just two lines of code - Feb 22, 2021.
EDA is a fundamental early process for any Data Science investigation. Typical approaches for visualization and exploration are powerful, but can be cumbersome for getting to the heart of your data. Now, you can get to know your data much faster with only a few lines of code... and it might even be fun!
- KDnuggets™ News 21:n07, Feb 17: We Don’t Need Data Scientists, We Need Data Engineers; Data Science vs Business Intelligence, Explained - Feb 17, 2021.
Do we need more data engineers than data scientists? Data Science vs Business Intelligence, Explained; Telling a Great Data Story: A Visualization Decision Tree; Essential Math for Data Science: Scalars and Vectors; 7 most recommended skills for a Data Scientist.
- 7 Most Recommended Skills to Learn to be a Data Scientist - Feb 10, 2021.
The Data Scientist professional has emerged as a true interdisciplinary role that spans a variety of skills, theoretical and practical. For the core, day-to-day activities, many critical requirements that enable the delivery of real business value reach well outside the realm of machine learning, and should be mastered by those aspiring to the field.
- KDnuggets™ News 21:n06, Feb 10: The Best Data Science Project to Have in Your Portfolio; Deep learning doesn’t need to be a black box - Feb 10, 2021.
The Best Data Science Project to Have in Your Portfolio; Deep learning doesn’t need to be a black box; Build Your First Data Science Application; How to create stunning visualizations using python from scratch; How to Get Your First Job in Data Science without Any Work Experience
- How to create stunning visualizations using python from scratch - Feb 4, 2021.
Data science and data analytics can be beautiful things. Not only because of the insights and enhancements to decision-making they can provide, but because of the rich visualizations about the data that can be created. Following this step-by-step guide using the Matplotlib and Seaborn libraries will help you improve the presentation and effective communication of your work.
- Getting Started with 5 Essential Natural Language Processing Libraries - Feb 3, 2021.
This article is an overview of how to get started with 5 popular Python NLP libraries, from those for linguistic data visualization, to data preprocessing, to multi-task functionality, to state of the art language modeling, and beyond.
- Creating Good Meaningful Plots: Some Principles - Jan 12, 2021.
Hera are some thought starters to help you create meaningful plots.
- How to Create Custom Real-time Plots in Deep Learning - Dec 14, 2020.
How to generate real-time visualizations of custom metrics while training a deep learning model using Keras callbacks.
- Top KDnuggets tweets, Dec 2-8: How to do visualization using #Python from scratch - Dec 9, 2020.
K-Means 8x faster, 27x lower error than Scikit-learn's in 25 lines; How to do visualization using #Python from scratch; Why the Future of ETL Is Not ELT, But EL(T); NoSQL for Beginners
- 20 Core Data Science Concepts for Beginners - Dec 8, 2020.
With so much to learn and so many advancements to follow in the field of data science, there are a core set of foundational concepts that remain essential. Twenty of these ideas are highlighted here that are key to review when preparing for a job interview or just to refresh your appreciation of the basics.
- 14 Data Science projects to improve your skills - Dec 1, 2020.
There's a lot of data out there and so many data science techniques to master or review. Check out these great project ideas from easy to advanced difficulty levels to develop new skills and strengthen your portfolio.
- Simple Python Package for Comparing, Plotting & Evaluating Regression Models - Nov 25, 2020.
This package is aimed to help users plot the evaluation metric graph with single line code for different widely used regression model metrics comparing them at a glance. With this utility package, it also significantly lowers the barrier for the practitioners to evaluate the different machine learning algorithms in an amateur fashion by applying it to their everyday predictive regression problems.
- TabPy: Combining Python and Tableau - Nov 24, 2020.
This article demonstrates how to get started using Python in Tableau.
- Top 6 Data Science Programs for Beginners - Nov 20, 2020.
Udacity has the best industry-leading programs in data science. Here are the top six data science courses for beginners to help you get started.
- Do’s and Don’ts of Analyzing Time Series - Nov 12, 2020.
When handling time series data in your Data Science analysis work, a variety of common mistakes are made that are basic, but very important, to the processing of this type of data. Here, we review these issues and recommend the best practices.
- 10 Underrated Python Skills - Oct 21, 2020.
Tips for feature analysis, hyperparameter tuning, data visualization and more.
- DOE SMART Visualization Platform 1.5M Prize Challenge - Oct 16, 2020.
The U.S. Department of Energy’s (DOE) Office of Fossil Energy (FE) will award up to $1.5 million to winning innovators in a prize challenge to support FE’s SMART initiative. Registration deadline to participate in the challenge is 11:59 p.m. EDT Friday, Jan 22, 2021.
- KDnuggets™ News 20:n38, Oct 7: 10 Essential Skills You Need to Know to Start Doing Data Science; The Best Free Data Science eBooks: 2020 Update - Oct 7, 2020.
Also: Comparing the Top Business Intelligence Tools: Power BI vs Tableau vs Qlik vs Domo; 5 Concepts Every Data Scientist Should Know; Understanding Transformers, the Data Science Way; 10 Best Machine Learning Courses in 2020
- Effective Visualization Techniques for Data Discovery and Analysis - Oct 6, 2020.
Learn how effective visual techniques help better explore and understand their data, discover trends and patterns, and communicate findings.
- Geographical Plots with Python - Sep 28, 2020.
When your data includes geographical information, rich map visualizations can offer significant value for you to understand your data and for the end user when interpreting analytical results.
- Statistical and Visual Exploratory Data Analysis with One Line of Code - Sep 21, 2020.
If EDA is not executed correctly, it can cause us to start modeling with “unclean” data. See how to use Pandas Profiling to perform EDA with a single line of code.
- Visualization Of COVID-19 New Cases Over Time In Python - Sep 15, 2020.
Inspired by another concise data visualization, the author of this article has crafted and shared the code for a heatmap which visualizes the COVID-19 pandemic in the United States over time.
- KDnuggets™ News 20:n34, Sep 9: Top Online Data Science Masters Degrees; Modern Data Science Skills: 8 Categories, Core Skills, and Hot Skills - Sep 9, 2020.
Also: Creating Powerful Animated Visualizations in Tableau; PyCaret 2.1 is here: What's new?; How To Decide What Data Skills To Learn; How to Evaluate the Performance of Your Machine Learning Model
- Modern Data Science Skills: 8 Categories, Core Skills, and Hot Skills - Sep 8, 2020.
We analyze the results of the Data Science Skills poll, including 8 categories of skills, 13 core skills that over 50% of respondents have, the emerging/hot skills that data scientists want to learn, and what is the top skill that Data Scientists want to learn.
- Creating Powerful Animated Visualizations in Tableau - Sep 7, 2020.
In this post we explore animated data visualization in Tableau,one of the tool's powerful features for making visualizations appealing and interactive.
- Data Science Tools Illustrated Study Guides - Aug 25, 2020.
These data science tools illustrated guides are broken up into four distinct categories: data retrieval, data manipulation, data visualization, and engineering tips. Both online and PDF versions of these guides are available.
- These Data Science Skills will be your Superpower - Aug 20, 2020.
Learning data science means learning the hard skills of statistics, programming, and machine learning. To complete your training, a broader set of soft skills will round out your capabilities as an effective and successful professional Data Scientist.
- Visualizing the Mobility Trends in European Countries Affected by COVID-19 - Aug 18, 2020.
This post highlights the movement of people from the 10 most-affected European countries based on the way they stay at home, work, and visit places, using Google's anonymized location tracking dataset.
- Bring your Pandas Dataframes to life with D-Tale - Aug 13, 2020.
Bring your Pandas dataframes to life with D-Tale. D-Tale is an open-source solution for which you can visualize, analyze and learn how to code Pandas data structures. In this tutorial you'll learn how to open the grid, build columns, create charts and view code exports.
- Build a Branded Web Based GIS Application Using R, Leaflet and Flexdashboard - Jun 24, 2020.
By using R, Flexdashboard and Leaflet, we can build a customized and branded web application to showcase location based data interactively across the organization. Instead of crowding the application with many widgets, we use menu tabs and pages to separate the interactive aspects.
- Looking Normal(ly Distributed) - May 20, 2020.
This article investigates when some probability distributions look normal "enough" for a statistical test.
- Top 10 Data Visualization Tools for Every Data Scientist - May 5, 2020.
At present, the data scientist is one of the most sought after professions. That’s one of the main reasons why we decided to cover the latest data visualization tools that every data scientist can use to make their work more effective.
- Outbreak Analytics: Data Science Strategies for a Novel Problem - Apr 30, 2020.
You walk down one aisle of the grocery store to get your favorite cereal. On the dairy aisle, someone sick from COVID-19 coughs. Did your decision to grab your cereal before your milk possibly keep you healthy? How can these unpredictable, near-random choices be included in complex models?
- Understanding the COVID-19 Pandemic Using Interactive Visualizations - Apr 29, 2020.
Interactive visualizations are an effective method for understanding the COVID-19 pandemic. This article presents a repository filled with just such insightful interactions.
- KDnuggets™ News 20:n13, Apr 1: Effective visualizations for pandemic storytelling; Machine learning for time series forecasting - Apr 1, 2020.
This week, read about the power of effective visualizations for pandemic storytelling; see how (not) to use machine learning for time series forecasting; learn about a deep learning breakthrough: a sub-linear deep learning algorithm that does not need a GPU?; familiarize yourself with how to painlessly analyze your time series; check out what can we learn from the latest coronavirus trends; and... KDnuggets topics?!? Also, much more.
- COVID-19 Visualized: The power of effective visualizations for pandemic storytelling - Mar 27, 2020.
Clear, succinct data visualizations can be powerful tools for telling stories and explaining phenomena. This article demonstrates this concept as relates to the COVID-19 pandemic.
- Coronavirus Data and Poll Analysis – yes, there is hope, if we act now - Mar 23, 2020.
We examine the growth of coronavirus daily cases in most affected countries, and show evidence that social distancing works in reducing the rate of spread. We also analyze KDnuggets Poll results - the scale of change to online and how Data Science work is likely to increase or drop in different regions. Stay Healthy and practice social distancing!
- The Berlin Rent Freeze: How many illegal overpriced offers can I find online? - Mar 10, 2020.
This post presents an analysis of Berlin online real estate listings, investigating a controversial law capping rents in the state, which went into effect on February 23. Are current landlords already respecting the new rent cap?
- Data Science Curriculum for self-study - Feb 26, 2020.
Are you asking the question, "how do I become a Data Scientist?" This list recommends the best essential topics to gain an introductory understanding for getting started in the field. After learning these basics, keep in mind that doing real data science projects through internships or competitions is crucial to acquiring the core skills necessary for the job.
- Graph Machine Learning Meets UX: An uncharted love affair - Jan 13, 2020.
When machine learning tools are developed by technology first, they risk failing to deliver on what users actually need. It can also be difficult for development teams to establish meaningful direction. This article explores the challenges of designing an interface that enables users to visualise and interact with insights from graph machine learning, and explores the very new, uncharted relationship between machine learning and UX.
- Top KDnuggets tweets, Jan 01-07: Introduction to Data Visualization and Storytelling: A Guide For The Data Scientist eBook - Jan 8, 2020.
Introduction to Data Visualization & Storytelling;The Data Science Interview Study Guide; Why Kaggle will NOT make you a great Data Scientist; Cartoon: Teaching Ethics to AI
- Plotnine: Python Alternative to ggplot2 - Dec 12, 2019.
Python's plotting libraries such as matplotlib and seaborn does allow the user to create elegant graphics as well, but lack of a standardized syntax for implementing the grammar of graphics compared to the simple, readable and layering approach of ggplot2 in R makes it more difficult to implement in Python.
- KDnuggets™ News 19:n46, Dec 4: The Future of Data Science Careers; Which Data Visualization Should I Use? - Dec 4, 2019.
This week: The Future of Careers in Data Science & Analysis; Task-based effectiveness of basic visualizations; Open Source Projects by Google, Uber and Facebook for Data Science and AI; Getting Started with Automated Text Summarization; A Non-Technical Reading List for Data Science; and much more!
- Vega-Lite: A grammar of interactive graphics - Dec 3, 2019.
Vega and Vega-lite follow in a long line of work that can trace its roots back to Wilkinson’s ‘The Grammar of Graphics.’ Since then VegaLite has come into existence, bringing high-level specification of interactive visualisations to the Vega-Lite world.
- Open Source Projects by Google, Uber and Facebook for Data Science and AI - Nov 28, 2019.
Open source is becoming the standard for sharing and improving technology. Some of the largest organizations in the world namely: Google, Facebook and Uber are open sourcing their own technologies that they use in their workflow to the public.
- Task-based effectiveness of basic visualizations - Nov 27, 2019.
This is a summary of a recent paper on an age-old topic: what visualisation should I use? No prizes for guessing “it depends!” Is this the paper to finally settle the age-old debate surrounding pie-charts??
- How to Visualize Data in Python (and R) - Nov 14, 2019.
Producing accessible data visualizations is a key data science skill. The following guidelines will help you create the best representations of your data using R and Python's Pandas library.
- Understanding Boxplots - Nov 8, 2019.
A boxplot. It can tell you about your outliers and what their values are. It can also tell you if your data is symmetrical, how tightly your data is grouped, and if and how your data is skewed.
- Top KDnuggets tweets, Oct 30 – Nov 05: Everything a Data Scientist Should Know About Data Management - Nov 6, 2019.
Which Data Science Skills are core and which are hot/emerging ones?; The 4 Quadrants of Data Science Skills and 7 Principles for Creating a Viral DataViz; Microsoft open sources #SandDance, a visual data exploration tool.
- KDnuggets™ News 19:n38, Oct 9: The Last SQL Guide for Data Analysis; 4 Quadrants of Data Science Skills and 7 steps for Viral Data Visualization - Oct 9, 2019.
Read a comprehensive SQL guide for data analysis; Learn how to choose the right clustering algorithm for your data; Find out how to create a viral DataViz using the data from Data Science Skills poll; Enroll in any of 10 Free Top Notch Natural Language Processing Courses; and more.
- The 4 Quadrants of Data Science Skills and 7 Principles for Creating a Viral Data Visualization - Oct 7, 2019.
As a data scientist, your most important skill is creating meaningful visualizations to disseminate knowledge and impact your organization or client. These seven principals will guide you toward developing charts with clarity, as exemplified with data from a recent KDnuggets poll.
- Which Data Science Skills are core and which are hot/emerging ones? - Sep 17, 2019.
We identify two main groups of Data Science skills: A: 13 core, stable skills that most respondents have and B: a group of hot, emerging skills that most do not have (yet) but want to add. See our detailed analysis.
- 5 Alternative Data Science Tools - Sep 17, 2019.
What other creative tools for data science beyond Python and R can you use to make an impression? It's not about the tool -- it's about its impact.
- Designing Dashboards that Users Actually Like – Free Webcast - Sep 6, 2019.
See how creating a system of purpose-specific displays enables users to quickly get answers to their data-related questions.
- Why Data Visualization Is The Most Important Skill in a Data Analyst Arsenal - Aug 26, 2019.
Visually-displayed data is much more accessible, and it’s critical to promptly identify the weaknesses of an organization, accurately forecast trading volumes and sale prices, or make the right business choices.
- The Easy Way to Do Advanced Data Visualisation for Data Scientists - Aug 13, 2019.
Creating effective data visualisations is a core skill for data scientists. This tutorial will guide you through how to easily develop interactive visualisations using the Python library plotly.
- South Dakota State University: Data Visualization Developer and Analyst [Brookings, SD] - Aug 2, 2019.
South Dakota State University is seeking a Data Visualization Developer and Analyst in Brookings, SD, to create business intelligence tools and reports to support the use of a campus-wide business intelligence and decision support system, compile multiple visualizations into intuitive dashboards for campus-wide use, and more.
- The Evolution of a ggplot - Jul 18, 2019.
A step-by-step tutorial showing how to turn a default ggplot into an appealing and easily understandable data visualization in R.
- Top KDnuggets tweets, Jul 10-16: Intuitive Visualization of Outlier Detection Methods; What’s wrong with the approach to Data Science? - Jul 17, 2019.
What's wrong with the approach to Data Science?; Intuitive Visualization of Outlier Detection Methods; The Death of Big Data and the Emergence of the Multi-Cloud Era
- How to Make Stunning 3D Plots for Better Storytelling - Jul 17, 2019.
3D Plots built in the right way for the right purpose are always stunning. In this article, we’ll see how to make stunning 3D plots with R using ggplot2 and rayshader.
- Annotated Heatmaps of a Correlation Matrix in 5 Simple Steps - Jul 9, 2019.
A heatmap is a graphical representation of data in which data values are represented as colors. That is, it uses color in order to communicate a value to the reader. This is a great tool to assist the audience towards the areas that matter the most when you have a large volume of data.
- Make your Data Talk! - Jun 28, 2019.
Matplotlib and Seaborn are two of the most powerful and popular data visualization libraries in Python. Read on to learn how to create some of the most frequently used graphs and charts using Matplotlib and Seaborn.
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- Do Conv-nets Dream of Psychedelic Sheep? - Jun 25, 2019.
In deep learning, understanding your model well enough to interpret its behavior will help improve model performance and reduce the black-box mystique of neural networks.
- Modelplotr v1.0 now on CRAN: Visualize the Business Value of your Predictive Models - Jun 21, 2019.
Explaining the business value of your predictive models to your business colleagues is a challenging task. Using Modelplotr, an R package, you can easily create stunning visualizations that clearly communicate the business value of your models.
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- KDnuggets™ News 19:n22, Jun 12: The Modern Open-Source Data Science/Machine Learning Ecosystem; Simplifying the Data Visualisation Process in Python - Jun 12, 2019.
The 6 tools in the modern open-source Data Science ecosystem; Simplifying the Data Visualisation Process in Python; The Infinity Stones of Data Science; Best resources for developers transitioning into data science.
- Using the ‘What-If Tool’ to investigate Machine Learning models - Jun 6, 2019.
The machine learning practitioner must be a detective, and this tool from teams at Google enables you to investigate and understand your models.
- PyViz: Simplifying the Data Visualisation Process in Python - Jun 6, 2019.
There are python libraries suitable for basic data visualizations but not for complicated ones, and there are libraries suitable only for complex visualizations. Is there a single library that handles both these tasks efficiently? The answer is yes. It's PyViz
- How to choose a visualization - Jun 4, 2019.
Visualizations based on the structure of data are needed during analysis, which might be different than for the end user. A new guide for choosing the right visualization helps you flexibly understand the data first.
- Animations with Matplotlib - May 30, 2019.
Animations make even more sense when depicting time series data like stock prices over the years, climate change over the past decade, seasonalities and trends since we can then see how a particular parameter behaves with time.
- 60+ useful graph visualization libraries - May 17, 2019.
We outline 60+ graph visualization libraries that allow users to build applications to display and interact with network representations of data.
- A Complete Exploratory Data Analysis and Visualization for Text Data: Combine Visualization and NLP to Generate Insights - May 9, 2019.
Visually representing the content of a text document is one of the most important tasks in the field of text mining as a Data Scientist or NLP specialist. However, there are some gaps between visualizing unstructured (text) data and structured data.
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- KDnuggets™ News 19:n16, Apr 24: Data Visualization in Python with Matplotlib & Seaborn; Getting Into Data Science: The Ultimate Q&A - Apr 24, 2019.
Best Data Visualization Techniques for small and large data; The Rise of Generative Adversarial Networks; Approach pre-trained deep learning models with caution; How Optimization Works; Building a Flask API to Automatically Extract Named Entities Using SpaCy
- Data Visualization in Python: Matplotlib vs Seaborn - Apr 19, 2019.
Seaborn and Matplotlib are two of Python's most powerful visualization libraries. Seaborn uses fewer syntax and has stunning default themes and Matplotlib is more easily customizable through accessing the classes.
- Best Data Visualization Techniques for small and large data - Apr 17, 2019.
Data visualization is used in many areas to model complex events and visualize phenomena that cannot be observed directly, such as weather patterns, medical conditions or mathematical relationships. Here we review basic data visualization tools and techniques.
- Because analysis is more than just dashboards - Apr 11, 2019.
Where traditional BI tools often make it easy to build dashboards, Mode makes it easy for you to answer any follow-up questions when you see changes in those dashboards. Choose the level of abstraction you want for a given dataset and quickly get to the story behind the change.
- KDnuggets™ News 19:n13, Apr 3: Top 10 Data Scientist Coding Mistakes; Explaining Random Forest®; Which Face is Real? - Apr 3, 2019.
Do you know when is using "for" loop a mistake? Read 10 top coding mistakes by Data Scientists; Understand Random Forests and Linear Regression with scikit-learn; Find how to choose the right chart type; and see if you can guess which face is real.
- 7 Qualities Your Big Data Visualization Tools Absolutely Must Have and 10 Tools That Have Them - Apr 2, 2019.
Without the right visualization tools, raw data is of little use. Data visualization helps present the data in an interactive visual format. Here are the qualities to look for in a data visualization tool.
- D3.js Graph Gallery for Data Visualization - Mar 28, 2019.
The d3 graph gallery is a collection of 200 simple charts made with d3.js, with reproducible, commented and editable code.
- How to Choose the Right Chart Type - Mar 27, 2019.
This article presents an infographic for choosing which chart type is most useful in a given scenario. The infographic and chart types are then explored for greater clarity.
- KDnuggets™ News 19:n12, Mar 27: My Best Tips for Agile Data Science Research; R vs Python for Data Visualization - Mar 27, 2019.
Tips for Agile Data Science Research, R (ggplot2) vs Python (Seaborn) Visualization, the problems with self-serve analytics, an approach to AI Blackbox explanation problem, a checklist for debugging neural nets, and more.
- R vs Python for Data Visualization - Mar 25, 2019.
This article demonstrates creating similar plots in R and Python using two of the most prominent data visualization packages on the market, namely ggplot2 and Seaborn.
- KDnuggets™ News 19:n07, Feb 13: The Best and Worst Data Visualizations of 2018; Gartner 2019 Magic Quadrant for Data Science Platforms - Feb 13, 2019.
Also: Data-science? Agile? Cycles?; How I used NLP (Spacy) to screen Data Science Resumes; Neural Networks - an Intuition; A Quick Guide to Feature Engineering; Understanding Gradient Boosting Machines
- The Best and Worst Data Visualizations of 2018 - Feb 8, 2019.
We reflect on some of the best examples of Data Visualization throughout 2018, before focussing on some of the not-so-good and how these can be improved.
- 6 Data Visualization Disasters – How to Avoid Them - Feb 5, 2019.
If you intend to use data visualizations in a presentation or publication, be certain that your audience will understand and trust the information. Here are six mistakes you will want to avoid.
- ELMo: Contextual Language Embedding - Jan 31, 2019.
Create a semantic search engine using deep contextualised language representations from ELMo and why context is everything in NLP.
- Airbnb Rental Listings Dataset Mining - Jan 28, 2019.
An Exploratory Analysis of Airbnb’s Data to understand the rental landscape in New York City.
- Top Active Blogs on AI, Analytics, Big Data, Data Science, Machine Learning – updated - Jan 14, 2019.
Stay up-to-date with the latest technological advancements using our extensive list of active blogs; this is a list of 100 recently active blogs on Big Data, Data Science, Data Mining, Machine Learning, and Artificial intelligence.
- KDnuggets™ News 19:n02, Jan 9: The cold start problem: how to build your machine learning portfolio; 5 Best Data Visualization Libraries - Jan 9, 2019.
Learn how to bootstrap your Machine Learning portfolio, which data visualization libraries to use, main approaches to ensemble learning, how to do text summarization, and check our special offers for leading analytics, AI, and Data Science events below.
- The Five Best Data Visualization Libraries - Jan 7, 2019.
There are plenty of library options out there to make great visualizations. We outline five of the best, complete with code examples and explanations, that will enable you to create and build interactive visualizations.
- Exploring the Data Jungle Free eBook - Dec 18, 2018.
This free eBook by Brian Godsey will provide you with real-world examples in Python, R, and other languages suitable for data science.
- Take a Look at Looker, Demo/Webinar Dec 13 - Dec 7, 2018.
Looker is designed for those building the next generation of data applications and analytic workflows. Join us for a live demonstration on Dec 13
- Common mistakes when carrying out machine learning and data science - Dec 6, 2018.
We examine typical mistakes in Data Science process, including wrong data visualization, incorrect processing of missing values, wrong transformation of categorical variables, and more. Learn what to avoid!
- Data Mining Book – Chapter Download - Dec 4, 2018.
Download this immediately useful book chapter, and learn how to create derived variables, which allow the statistical and Data Science modeling to incorporate human insights.
- Graph-Powered Machine Learning - Dec 3, 2018.
This book from Manning Publications is a wonderful introduction to graphs for machine learning enthusiasts, as well as a great entrée into machine learning for graph experts.
- Best Machine Learning Languages, Data Visualization Tools, DL Frameworks, and Big Data Tools - Dec 3, 2018.
We cover a variety of topics, from machine learning to deep learning, from data visualization to data tools, with comments and explanations from experts in the relevant fields.
- SQL, Python, and R in One Platform - Nov 27, 2018.
Stop jumping between applications. Get a complete analytical toolkit.
- Data Mining Book – Chapter Download - Nov 2, 2018.
Download this immediately useful book chapter, and learn how to create derived variables, which allow the statistical and Data Science modeling to incorporate human insights.
- SQL, Python, & R in One Platform - Oct 26, 2018.
No more jumping between applications. Mode Studio combines a SQL editor, Python and R notebooks, and a visualization builder in one platform.