- KDnuggets™ News 20:n36, Sep 23: New Poll: What Python IDE / Editor you used the most in 2020?; Automating Every Aspect of Your Python Project - Sep 23, 2020.
New Poll: What Python IDE / Editor you used the most in 2020?; Automating Every Aspect of Your Python Project; Autograd: The Best Machine Learning Library You're Not Using?; Implementing a Deep Learning Library from Scratch in Python; Online Certificates/Courses in AI, Data Science, Machine Learning; Can Neural Networks Show Imagination?
Automation, Certificate, Courses, Data Science, Deep Learning, DeepMind, Machine Learning, Neural Networks, Python
- New Poll: What Python IDE / Editor you used the most in 2020? - Sep 22, 2020.
The latest KDnuggets polls asks which Python IDE / Editor you have used the most in 2020. Participate now, and share your experiences with the community.
Data Science, Development, IDE, Poll, Programming, Python
- How to Effectively Obtain Consumer Insights in a Data Overload Era - Sep 17, 2020.
Everybody knows how important is understanding your customer, but how to do that in an era of Information Overload?
Analytics, Customer Analytics, Data Science
- Lessons From My First Kaggle Competition - Sep 14, 2020.
How I chose my first Kaggle competition to enter and what I learned from doing it.
Competition, Data Science, Kaggle
Statistics with Julia: The Free eBook - Sep 14, 2020.
This free eBook is a draft copy of the upcoming Statistics with Julia: Fundamentals for Data Science, Machine Learning and Artificial Intelligence. Interested in learning Julia for data science? This might be the best intro out there.
Books, Data Science, Free ebook, Julia, Statistics
- Feature Engineering for Numerical Data - Sep 11, 2020.
Data feeds machine learning models, and the more the better, right? Well, sometimes numerical data isn't quite right for ingestion, so a variety of methods, detailed in this article, are available to transform raw numbers into something a bit more palatable.
Data Preparation, Data Science, Feature Engineering
- AI Papers to Read in 2020 - Sep 10, 2020.
Reading suggestions to keep you up-to-date with the latest and classic breakthroughs in AI and Data Science.
AI, Attention, Convolutional Neural Networks, Data Science, GANs, Neural Networks, Reformer, Research
- 6 Common Mistakes in Data Science and How To Avoid Them - Sep 10, 2020.
As a novice or seasoned Data Scientist, your work depends on the data, which is rarely perfect. Properly handling the typical issues with data quality and completeness is crucial, and we review how to avoid six of these common scenarios.
Advice, Data Quality, Data Science, Hyperparameter, Mistakes, Overfitting
- Let’s Be Honest: We’re Drowning in Data - Sep 10, 2020.
The fields of Big Data, Data Analytics/Science, and Data Integration need to face a new truth: We are drowning in data, more and more so every second of every day.
Big Data, Data Analytics, Data Science
- 4 Tools to Speed Up Your Data Science Writing - Sep 9, 2020.
This article covers how you can achieve your writing goals with these 4 tools.
Advice, Data Science, GitHub, Jupyter
- 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
Data Science, Data Science Skills, Data Visualization, Machine Learning, Master of Science, Modeling, Online Education, PyCaret, Tableau
- 9 Developing Data Science & Analytics Job Trends - Sep 7, 2020.
With so much disruption in 2020 already, a recent report by Burtch Works looks ahead to next year and beyond, and shares insights about how today's hiring market trends may impact our work lives for years to come.
Analytics, Burtch Works, Career, COVID-19, Data Science, Jobs, Trends
- Data Scientists think data is their #1 problem. Here’s why they’re wrong. - Sep 4, 2020.
We tend to think it's all about the data. However, for real data science projects at real organizations in real life, there are more fundamental aspects to consider to do data science right.
Business, Data Science, Mistakes, Problem Definition
Top Online Masters in Analytics, Business Analytics, Data Science – Updated - Sep 1, 2020.
We provide an updated list of best online Masters in AI, Analytics, and Data Science, including rankings, tuition, and duration of the education program.
Data Analytics, Data Science, Education, Master of Science, MS in Analytics, MS in Data Science, Online Education
- Data is everywhere and it powers everything we do! - Aug 28, 2020.
In this article I would like to focus on how companies can start their data-centric strategies and how to achieve success in their data transformation journeys. Have tried to share my thoughts why companies have to consider data at its epitome for their growth, for being competitive, for being smarter, innovative and be prepared for any unforeseen market surprises.
Analytics, Business, Data Science
- How Data Science Is Keeping People Safe During COVID-19 - Aug 25, 2020.
Data, and more importantly, the way people use it, is shaping and refining approaches to COVID-19 safety. Here's a closer look at how this is happening.
Coronavirus, COVID-19, Data Science, Safety
- 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.
Cheat Sheet, Data Preprocessing, Data Processing, Data Science, Data Science Tools, Data Visualization, Python, R, SQL
- Data Science Meets Devops: MLOps with Jupyter, Git, and Kubernetes - Aug 21, 2020.
An end-to-end example of deploying a machine learning product using Jupyter, Papermill, Tekton, GitOps and Kubeflow.
Data Science, DevOps, Jupyter, Kubeflow, Kubernetes, MLOps
- KDD-2020 (virtual), the leading conference on Data Science and Knowledge Discovery, Aug 23-27 – register now - Aug 18, 2020.
Using an interactive VR platform, KDD-2020 brings you the latest research in AI, Data Science, Deep Learning, and Machine Learning with tutorials to improve your skills, keynotes from top experts, workshops on state-of-the-art topics and over 200 research presentations.
ACM SIGKDD, COVID-19, Data Science, Deep Learning, KDD, KDD-2020, Machine Learning, Meetings, Research
The List of Top 10 Lists in Data Science - Aug 14, 2020.
The list of Top 10 lists that Data Scientists -- from enthusiasts to those who want to jump start a career -- must know to smoothly navigate a path through this field.
Algorithms, Data Science, Data Science Skills, Datasets, Influencers, LinkedIn, Python, Top 10
- 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.
Data Exploration, Data Science, Data Visualization, Pandas, Python
Going Beyond Superficial: Data Science MOOCs with Substance - Aug 13, 2020.
Data science MOOCs are superficial. At least, a lot of them are. What are your options when looking for something more substantive?
Courses, Data Science, Machine Learning, MOOC
- Introduction to Statistics for Data Science - Aug 12, 2020.
Statistics is foundational for Data Science and a crucial skill to master for any practitioner. This advanced introduction reviews with examples the fundamental concepts of inferential statistics by illustrating the differences between Point Estimators and Confidence Intervals Estimates.
Beginners, Data Science, Statistics
- How Natural Language Processing Is Changing Data Analytics - Aug 12, 2020.
As it becomes more prevalent, NLP will enable humans to interact with computers in ways not possible before. This new type of collaboration will allow improvements in a wide variety of human endeavors, including business, philanthropy, health, and communication.
Data Analytics, Data Science, NLP
- Unit Test Your Data Pipeline, You Will Thank Yourself Later - Aug 11, 2020.
While you cannot test model output, at least you should test that inputs are correct. Compared to the time you invest in writing unit tests, good pieces of simple tests will save you much more time later, especially when working on large projects or big data.
Data Science, Pipeline, Programming
- Data Science Internship Interview Questions - Aug 11, 2020.
Data science is an attractive field because not only is it lucrative, but you can have opportunities to work on interesting projects, and you’re always learning new things. If you're trying to get started from the ground up, then review this guide to prepare for the interview essentials.
Data Science, Internship, Interview Questions
- HOSTKEY GPU Grant Program - Aug 10, 2020.
The HOSTKEY GPU Grant Program is open to specialists and professionals in the Data Science sector performing research or other projects centered on innovative uses of GPU processing and which will glean practical results in the field of Data Science, with the objective of supporting basic scientific research and prospective startups.
Data Science, GPU, Research
- The Uncommon Data Science Job Guide - Aug 7, 2020.
With the job landscape in Data Science becoming hyper-competitive, there are clear strategies you can consider to find your way to snagging a position in the field.
Career, Career Advice, Data Science, Jobs
- New Poll: Which Data Science Skills You Have and Which Ones You Want? Vote Now - Aug 5, 2020.
Take part in the latest KDnuggets poll, and share your insights with the community. Which Data Science skills do you currently possess, and which are you looking forward to add or improve upon? Vote now!
Career, Data Science, Data Science Skills, Poll, Skills
- 5 Apache Spark Best Practices For Data Science - Aug 4, 2020.
Check out these best practices for Spark that the author wishes they knew before starting their project.
Apache Spark, Best Practices, Data Science
Know What Employers are Expecting for a Data Scientist Role in 2020 - Aug 3, 2020.
The analysis is done from 1000+ recent Data scientist jobs, extracted from job portals using web scraping.
Career Advice, Data Science, Data Scientist
First Steps of a Data Science Project - Jul 29, 2020.
Many data science projects are launched with good intentions, but fail to deliver because the correct process is not understood. To achieve good performance and results in this work, the first steps must include clearly defining goals and outcomes, collecting data, and preparing and exploring the data. This is all about solving problems, which requires a systematic process.
Beginners, Data Exploration, Data Preparation, Data Science
- Labelling Data Using Snorkel - Jul 24, 2020.
In this tutorial, we walk through the process of using Snorkel to generate labels for an unlabelled dataset. We will provide you examples of basic Snorkel components by guiding you through a real clinical application of Snorkel.
Data Labeling, Data Science, Deep Learning, Machine Learning, NLP, Python
Data Science MOOCs are too Superficial - Jul 20, 2020.
Most massive open online courses are too superficial because they offer introductory-level courses. For in-depth knowledge, more is needed to increase your knowledge and expertise after establishing a foundation.
Data Science, MOOC, Online Education
- Foundations of Data Science: The Free eBook - Jul 13, 2020.
As has become tradition on KDnuggets, let's start a new week with a new eBook. This time we check out a survey style text with a variety of topics, Foundations of Data Science.
Data Science, Free ebook
- Why Learn Python? Here Are 8 Data-Driven Reasons - Jul 10, 2020.
Through this blog, I will list out the major reasons why you should learn Python and the 8 major data-driven reasons for learning it.
Data Science, Programming, Programming Languages, Python
A Layman’s Guide to Data Science. Part 3: Data Science Workflow - Jul 6, 2020.
Learn and appreciate the typical workflow for a data science project, including data preparation (extraction, cleaning, and understanding), analysis (modeling), reflection (finding new paths), and communication of the results to others.
Beginners, Data Science, Data Workflow, Sciforce, Workflow
- Data Cleaning: The secret ingredient to the success of any Data Science Project - Jul 1, 2020.
With an uncleaned dataset, no matter what type of algorithm you try, you will never get accurate results. That is why data scientists spend a considerable amount of time on data cleaning.
Data Cleaning, Data Preparation, Data Science, Outliers, Python
- Software engineering fundamentals for Data Scientists - Jun 30, 2020.
As a data scientist writing code for your models, it's quite possible that your work will make its way into a production environment to be used by the masses. But, writing code that is deployed as software is much different than writing code for exploratory data analysis. Learn about the key approaches for making your code production-ready that will save you time and future headaches.
Advice, Best Practices, Data Science, Programming, Software Engineering
- KDnuggets™ News 20:n25, Jun 24: PyTorch Fundamentals You Should Know; Free Math Courses to Boost Your Data Science Skills - Jun 24, 2020.
A Classification Project in Machine Learning: a gentle step-by-step guide; Crop Disease Detection Using Machine Learning and Computer Vision; Bias in AI: A Primer; Machine Learning in Dask; How to Deal with Missing Values in Your Dataset
Agriculture, Computer Vision, Courses, Data Science, Machine Learning, Mathematics, PyTorch, Tom Fawcett
Five Cognitive Biases In Data Science (And how to avoid them) - Jun 12, 2020.
Everyone is prey to cognitive biases that skew thinking, but data scientists must prevent them from spoiling their work. Learn more about five biases that can all too easily make your seemingly objective work become surprisingly subjective.
Advice, Bias, Cognitive Bias, Confirmation Bias, Data Science
- Top 6 Reasons Data Scientists Should Know Java - Jun 12, 2020.
There are many reasons why data scientists should learn Java. Read this overview of 6 specific reasons to help decide if Java might be right for your projects.
Data Science, Data Scientist, Java
- 3 Key Data Science Questions to Ask Your Big Data - Jun 3, 2020.
The process of understanding your data begins by asking 3 questions at the highest level, and then iteratively asking hundreds of cascading questions to get deeper insights.
Big Data, Business, Customer Analytics, Data Science, Metrics
- Best GIS Courses in 2020 - May 27, 2020.
Geographic Information Systems Analysis is the analysis of spatial relationships and patterns. Spatial components are being ingrained into society with the advent of the Internet of Things (IoT) in which more data can be connected and is likely to have a spatio-temporal component as well.
Data Science, Geospatial, GIS, MOOC
- Appropriately Handling Missing Values for Statistical Modelling and Prediction - May 22, 2020.
Many statisticians in industry agree that blindly imputing the missing values in your dataset is a dangerous move and should be avoided without first understanding why the data is missing in the first place.
Advice, Analytics, Business Analytics, Data Preparation, Data Science, Data Scientist, Missing Values, Statistics
- Complex logic at breakneck speed: Try Julia for data science - May 20, 2020.
We show a comparative performance benchmarking of Julia with an equivalent Python code to show why Julia is great for data science and machine learning.
Benchmark, Data Science, Julia, numpy, Python
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.
Data Science, Data Science Tools, Data Scientist, Data Visualization
- 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?
Alteryx, Coronavirus, COVID-19, Data Science, Data Visualization, Forecasting
- Exploring the Impact of Geographic Information Systems - Apr 30, 2020.
GIS has mostly been behind more popular buzzwords like machine learning and deep learning. GIS has always been around us in the background being used in government, business, medicine, real estate, transport, manufacturing etc.
Data Science, Geospatial, GIS
Five Cool Python Libraries for Data Science - Apr 30, 2020.
Check out these 5 cool Python libraries that the author has come across during an NLP project, and which have made their life easier.
Data Science, NLP, Python
Should Data Scientists Model COVID19 and other Biological Events - Apr 22, 2020.
Biostatisticians use statistical techniques that your current everyday data scientists have probably never heard of. This is a great example where lack of domain knowledge exposes you as someone that does not know what they are doing and are merely hopping on a trend.
Advice, COVID-19, Data Science, Data Scientist, Statistics
- Free High-Quality Machine Learning & Data Science Books & Courses: Quarantine Edition - Apr 22, 2020.
If you find yourself quarantined and looking for free learning materials in the way of books and courses to sharpen your data science and machine learning skills, this collection of articles I have previously written curating such things is for you.
Books, Courses, Data Science, Free ebook, Machine Learning, MOOC
- Dockerize Jupyter with the Visual Debugger - Apr 17, 2020.
A step by step guide to enable and use visual debugging in Jupyter in a docker container.
Data Science, Docker, Jupyter, Python
- Can Java Be Used for Machine Learning and Data Science? - Apr 14, 2020.
While Python and R have become favorites for building these programs, many organizations are turning to Java application development to meet their needs. Read on to see how, and why.
Data Science, Java, Machine Learning, Programming Languages
- Peer Reviewing Data Science Projects - Apr 13, 2020.
In any technical development field, having other practitioners review your work before shipping code off to production is a valuable support tool to make sure your work is error-proof. Even through your preparation for the review, improvements might be discovered and then other issues that escaped your awareness can be spotted by outsiders. This peer scrutiny can also be applied to Data Science, and this article outlines a process that you can experiment with in your team.
Advice, Checklist, Data Science, Deployment, KPI
- How Data Science Is Being Used to Understand COVID-19 - Apr 10, 2020.
Read this overview to gain an understanding of how data scientists are working hard to learn as much about COVID-19 as they can.
Coronavirus, Data Science, Healthcare
- 3 Best Sites to Find Datasets for your Data Science Projects - Apr 9, 2020.
When first learning data science, you will inevitably find yourself looking for more datasets to practice with. Here, we recommend the 3 best sites to find datasets to spark your next data science project.
Coronavirus, Data, Data Science, Datasets, Kaggle
- A Layman’s Guide to Data Science. Part 2: How to Build a Data Project - Apr 2, 2020.
As Part 2 in a Guide to Data Science, we outline the steps to build your first Data Science project, including how to ask good questions to understand the data first, how to prepare the data, how to develop an MVP, reiterate to build a good product, and, finally, present your project.
Advice, Beginners, Data Preparation, Data Science, Sciforce
- Why you should NOT use MS MARCO to evaluate semantic search - Apr 2, 2020.
If we want to investigate the power and limitations of semantic vectors (pre-trained or not), we should ideally prioritize datasets that are less biased towards term-matching signals. This piece shows that the MS MARCO dataset is more biased towards those signals than we expected and that the same issues are likely present in many other datasets due to similar data collection designs.
Data Science, Metrics, NLP, Text Analytics
- Advice for a Successful Data Science Career - Mar 30, 2020.
This blog is meant to show that most everyone has had to expend quite a bit of effort to get where they are. They have to work hard, sometimes experience failure, show discipline, be persistent, be dedicated to their goals, and sometimes sacrifice or take risks.
Career Advice, Data Science
- Making sense of ensemble learning techniques - Mar 26, 2020.
This article breaks down ensemble learning and how it can be used for problem solving.
Algorithms, Data Science, Ensemble Methods, Machine Learning
- Diffusion Map for Manifold Learning, Theory and Implementation - Mar 25, 2020.
This article aims to introduce one of the manifold learning techniques called Diffusion Map. This technique enables us to understand the underlying geometric structure of high dimensional data as well as to reduce the dimensions, if required, by neatly capturing the non-linear relationships between the original dimensions.
Data Preparation, Data Science, Dimensionality Reduction, Feature Engineering, Machine Learning
- Scaling Your Data Strategy - Mar 17, 2020.
This article presents a particular vision for a cohesive data strategy for addressing large-scale problems with data-driven solutions, based on prior professional experiences.
Data Science, Scalability, Strategy
50 Must-Read Free Books For Every Data Scientist in 2020 - Mar 9, 2020.
In this article, we are listing down some excellent data science books which cover the wide variety of topics under Data Science.
Books, Data Science, Data Scientist, Free ebook
- Resources for Women in AI, Data Science, and Machine Learning - Mar 8, 2020.
For the international women's day, we feature resources to help more women enter and succeed in AI, Big Data, Data Science, and Machine Learning fields.
AI, Data Science, Diversity, Machine Learning, Women
- How do we Better Solve Analytics Problems? - Mar 4, 2020.
Problem definition and solution development are key ingredients of being a consultant. Structuring the problem definition phase is critical to project success but may seem like a creative process.
Business Analytics, Data Analytics, Data Science
- The Augmented Scientist Part 1: Practical Application Machine Learning in Classification of SEM Images - Mar 3, 2020.
Our goal here is to see if we can build a classifier that can identify patterns in Scanning Electron Microscope (SEM) images, and compare the performance of our classifier to the current state-of-the-art.
Data Science, Data Scientist, Image Classification, Machine Learning
20 AI, Data Science, Machine Learning Terms You Need to Know in 2020 (Part 2) - Mar 2, 2020.
We explain important AI, ML, Data Science terms you should know in 2020, including Double Descent, Ethics in AI, Explainability (Explainable AI), Full Stack Data Science, Geospatial, GPT-2, NLG (Natural Language Generation), PyTorch, Reinforcement Learning, and Transformer Architecture.
AI, Data Science, Explainability, Geospatial, GPT-2, Key Terms, Machine Learning, Natural Language Generation, Reinforcement Learning, Transformer
- 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.
Advice, Data Science, Data Science Education, Data Visualization, Mathematics, Probability, Programming, Statistics
Python and R Courses for Data Science - Feb 26, 2020.
Since Python and R are a must for today's data scientists, continuous learning is paramount. Online courses are arguably the best and most flexible way to upskill throughout ones career.
Coursera, Data Science, edX, MOOC, Programming, Python, R
- Probability Distributions in Data Science - Feb 26, 2020.
Some machine learning models are designed to work best under some distribution assumptions. Therefore, knowing with which distributions we are working with can help us to identify which models are best to use.
Data Science, Distribution, Normal Distribution, Probability
Free Mathematics Courses for Data Science & Machine Learning - Feb 25, 2020.
It's no secret that mathematics is the foundation of data science. Here are a selection of courses to help increase your maths skills to excel in data science, machine learning, and beyond.
Courses, Data Science, Machine Learning, Mathematics, MOOC
- Getting Started with R Programming - Feb 19, 2020.
An end to end Data Analysis using R, the second most requested programming language in Data Science.
Data Science, Machine Learning, Programming, R
- 20 AI, Data Science, Machine Learning Terms You Need to Know in 2020 (Part 1) - Feb 18, 2020.
2020 is well underway, and we bring you 20 AI, data science, and machine learning terms we should all be familiar with as the year marches onward.
AI, Data Science, Key Terms, Machine Learning
- Fourier Transformation for a Data Scientist - Feb 14, 2020.
The article contains a brief intro into Fourier transformation mathematically and its applications in AI.
Data Science, Data Scientist, Mathematics, Python
- Fidelity on How to Find a Tailor-Fit Unicorn Data Scientist - Feb 11, 2020.
Predictive Analytics World for Financial Services in Las Vegas, May 31-Jun 4 is honored to host an exceptional keynote by Fidelity Investments’ AI and Data Science Center of Excellence Leader, Victor Lo: "How to Find a Tailor-Fit 'Unicorn' Data Scientist for Financial Services". Use the code KDNUGGETS for a 15% discount on your Predictive Analytics World ticket.
Data Science, PAW, Predictive Analytics World, Unicorn
- The Data Science Puzzle — 2020 Edition - Feb 7, 2020.
The data science puzzle is once again re-examined through the relationship between several key concepts of the landscape, incorporating updates and observations since last time. Check out the results here.
AI, Big Data, Data Mining, Data Science, Deep Learning, Machine Learning
Data Validation for Machine Learning - Jan 31, 2020.
While the validation process cannot directly find what is wrong, the process can show us sometimes that there is a problem with the stability of the model.
Cross-validation, Data Science, Machine Learning
- Google Dataset Search Provides Access to 25 Million Datasets - Jan 29, 2020.
Google's dataset search is out of beta, and provides centralized access to 25 million datasets.
Data Science, Datasets, Google, Search
- Data Scientist Archetypes - Jan 28, 2020.
My goal here is to give you a map for navigating the sprawling terrain of data science. It’s to help you prioritize what you want to learn and what you want to do, so you don’t feel lost.
Career Advice, Data Science, Data Scientist
- The Decade of Data Science - Jan 27, 2020.
With the last decade being so strong for the emerging field of Data Science, this review considers current trends in the industry, popular frameworks, helpful tools, and new tools that can be leveraged more in the future.
Containers, Data Science, Transfer Learning, Trends
- What Do Data Scientists in Europe Do & How Much Are They Worth? - Jan 23, 2020.
Interested in knowing what a data scientist is worth in Europe, and what one does? Read this overview of a recent survey on the topic and gain some insight into the European data science professional job market.
Data Science, Europe, Salary
- The Data Science Interview Study Guide - Jan 22, 2020.
Preparing for a job interview can be a full-time job, and Data Science interviews are no different. Here are 121 resources that can help you study and quiz your way to landing your dream data science job.
Career Advice, Data Science, Interview Questions
- Top 9 Mobile Apps for Learning and Practicing Data Science - Jan 17, 2020.
This article will tell you about the top 9 mobile apps that help the user in learning and practicing data science and hence is improving their productivity.
Apps, Data Science, Mobile
- Handling Trees in Data Science Algorithmic Interview - Jan 16, 2020.
This post is about fast-tracking the study and explanation of tree concepts for the data scientists so that you breeze through the next time you get asked these in an interview.
Algorithms, Data Science, Decision Trees, Interview Questions
- 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.
Data Science, Data Visualization, Design, Graph Analytics, Machine Learning, UI/UX
- 7 Steps to a Job-winning Data Science Resume - Jan 10, 2020.
A resume plays a key role in bagging that dream data science job. We break down the nuances of a job-winning data science resume so that you can go ahead and transform your own resume.
Career Advice, Careers, Data Science, Resume
7 Resources to Becoming a Data Engineer - Jan 7, 2020.
An estimated 8,650% growth of the volume of Data to 175 zetabytes from 2010 to 2025 has created an enormous need for Data Engineers to build an organization's big data platform to be fast, efficient and scalable.
Advice, Big Data, Cloud Computing, Data Engineering, Data Science, MOOC, SQL
- Why Python is One of the Most Preferred Languages for Data Science? - Jan 3, 2020.
Why do most data scientists love Python? Learn more about how so many well-developed Python packages can help you accomplish your crucial data science tasks.
Data Exploration, Data Science, Programming Languages, Python
- How HR Is Using Data Science and Analytics to Close the Gender Gap - Jan 3, 2020.
The gender gap can extend to the lack of equal representation in certain industries or career paths, and there's an extraordinarily long way to go before people will be on equal footing in the labor market. Human resources professionals can rely on data analytics to make progress.
Analytics, Data Science, Gender, HR
How To “Ultralearn” Data Science: summary, for those in a hurry - Dec 30, 2019.
For those of you in a hurry and interested in ultralearning (which should be all of you), this recap reviews the approach and summarizes its key elements -- focus, optimization, and deep understanding with experimentation -- geared toward learning Data Science.
Advice, Data Science, Experimentation, Optimization, Ultralearn
- How To “Ultralearn” Data Science: deep understanding and experimentation, Part 4 - Dec 27, 2019.
In this fourth and final part of the ultralearning data science series, it's time to take the final steps toward developing a deep understanding of the fundamentals and learning how to experiment -- the two aspects that are the ultimate keys to ultralearning.
Advice, Data Science, Experimentation, Ultralearn
What is a Data Scientist Worth? - Dec 23, 2019.
What is the Salary of a Data Scientist in 2019? Let's have a look at some data to see how we can answer that question.
Data Science, Salary, StackOverflow
- The Most In Demand Tech Skills for Data Scientists - Dec 20, 2019.
By the end of this article you’ll know which technologies are becoming more popular with employers and which are becoming less popular.
Career Advice, Data Science, Data Science Skills, Data Scientist
- Alternative Cloud Hosted Data Science Environments - Dec 19, 2019.
Over the years new alternative providers have risen to provided a solitary data science environment hosted on the cloud for data scientist to analyze, host and share their work.
Big Data, Cloud Computing, Data Science, Jupyter, Saturn Cloud
- How To “Ultralearn” Data Science: removing distractions and finding focus, Part 2 - Dec 17, 2019.
This second part in a series about how to "ultralearn" data science will guide you through several techniques to remove those distractions -- because your focus needs more focus.
Beginners, Data Science, Education, Ultralearn
- How To “Ultralearn” Data Science, Part 1 - Dec 13, 2019.
What is "ultralearning" and how can you follow the strategy to become an expert of data science? Start with this first part in a series that will guide you through this self-motivated methodology to help you efficiently master difficult skills.
Beginners, Data Science, Education, Ultralearn
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.
Data Science, Data Visualization, Python, R
- AI, Analytics, Machine Learning, Data Science, Deep Learning Technology Main Developments in 2019 and Key Trends for 2020 - Dec 11, 2019.
We asked leading experts - what are the most important developments of 2019 and 2020 key trends in AI, Analytics, Machine Learning, Data Science, and Deep Learning? This blog focuses mainly on technology and deployment.
2020 Predictions, AI, Analytics, Bill Schmarzo, Carla Gentry, Data Science, Doug Laney, Jen Underwood, Kate Strachnyi, Machine Learning, Meta Brown, Ronald van Loon, Tom Davenport, Trends
- The 4 Hottest Trends in Data Science for 2020 - Dec 9, 2019.
The field of Data Science is growing with new capabilities and reach into every industry. With digital transformations occurring in organizations around the world, 2019 included trends of more companies leveraging more data to make better decisions. Check out these next trends in Data Science expected to take off in 2020.
2020 Predictions, Automated Data Science, AutoML, Cloud Computing, Data Science, NLP, Privacy, Security, Trends
- AI, Analytics, Machine Learning, Data Science, Deep Learning Research Main Developments in 2019 and Key Trends for 2020 - Dec 9, 2019.
As we say goodbye to one year and look forward to another, KDnuggets has once again solicited opinions from numerous research & technology experts as to the most important developments of 2019 and their 2020 key trend predictions.
2020 Predictions, AI, Ajit Jaokar, Analytics, Andriy Burkov, Anima Anandkumar, Daniel Tunkelang, Data Science, Deep Learning, Machine Learning, Pedro Domingos, Research, Rosaria Silipo, Xavier Amatriain
- The Rise of User-Generated Data Labeling - Dec 4, 2019.
Let’s say your project is humongous and needs data labeling to be done continuously - while you’re on-the-go, sleeping, or eating. I’m sure you’d appreciate User-generated Data Labeling. I’ve got 6 interesting examples to help you understand this, let’s dive right in!
Data Labeling, Data Preparation, Data Science, User Generated Content
- Data Science Curriculum Roadmap - Dec 3, 2019.
What follows is a set of broad recommendations, and it will inevitably require a lot of adjustments in each implementation. Given that caveat, here are our curriculum recommendations.
Data Science, Data Science Education
- A Non-Technical Reading List for Data Science - Dec 2, 2019.
The world still cannot be reduced to numbers on a page because human beings are still the ones making all the decisions. So, the best data scientists understand the numbers and the people. Check out these great data science books that will make you a better data scientist without delving into the technical details.
Books, Data Science, Future, Review, Society
- Top 7 Data Science Use Cases in Trust and Security - Dec 2, 2019.
What are trust and safety? What is the role of trust and security in the modern world? Read this overview of 7 data science application use cases in the realm of trust and security.
AI, Data Science, Security, Trust, Use Cases
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.
Advice, AI, Data Science, Data Scientist, Data Visualization, Deep Learning, Facebook, Google, Open Source, Python, Uber
The Future of Careers in Data Science & Analysis - Nov 27, 2019.
As the fields of data science and analysis continue to expand, the next crop of bright minds is always needed. Learn more about the nuances of these jobs and find where you can fit in for a rewarding and interesting career.
Careers, Data Analyst, Data Science, Data Scientist
- Top 8 Data Science Use Cases in Marketing - Nov 25, 2019.
In this article, we want to highlight some key data science use cases in marketing. Let us concentrate on several instances that present particular interest and managed to prove their efficiency in the course of time.
Data Science, Marketing, Use Cases
- Reproducibility, Replicability, and Data Science - Nov 19, 2019.
As cornerstones of scientific processes, reproducibility and replicability ensure results can be verified and trusted. These two concepts are also crucial in data science, and as a data scientist, you must follow the same rigor and standards in your projects.
Best Practices, Data Science, Overfitting, Reproducibility, Trust, Validation
- What is Data Science? - Nov 8, 2019.
Data Science is pitched as a modern and exciting job offering high satisfaction. Does its reality really live up to the hype? Here, we show what it's really like to work as a Data Scientist.
Career, Data Science, Data Science Skills, Explained
- Set Operations Applied to Pandas DataFrames - Nov 7, 2019.
In this tutorial, we show how to apply mathematical set operations (union, intersection, and difference) to Pandas DataFrames with the goal of easing the task of comparing the rows of two datasets.
Data Preparation, Data Science, Pandas, Python
- Data Sources 101 - Oct 28, 2019.
Data collection is one of the first steps of the data lifecycle — you need to get all the data you require in the first place. To collect the right data, you need to know where to find it and determine the effort involved in collecting it. This article answers the most basic question: where does all the data you need (or might need) come from?
Big Data, Data Science, Datasets, Unstructured data
- How to Write Web Apps Using Simple Python for Data Scientists - Oct 22, 2019.
Convert your Data Science Projects into cool apps easily without knowing any web frameworks.
Apps, Data Science, Data Scientist, Python
- Top 7 Things I Learned in my Data Science Masters - Oct 15, 2019.
Even though I’m still in my studies, here’s a list of the most important things I’ve learned (as of yet).
Data Science, Data Science Education, Tips
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.
Data Science, Data Science Skills, Data Visualization, Excel, Java, Python, Skills, TensorFlow
The Last SQL Guide for Data Analysis You’ll Ever Need - Oct 4, 2019.
This is it: the last SQL guide for data analysis you'll ever need! OK, maybe it’s actually the first. But it’ll give you a solid head start.
Cheat Sheet, Data Analysis, Data Science, SQL
- Data Preparation for Machine learning 101: Why it’s important and how to do it - Oct 2, 2019.
As data scientists who are the brains behind the AI-based innovations, you need to understand the significance of data preparation to achieve the desired level of cognitive capability for your models. Let’s begin.
Data Preparation, Data Science, Machine Learning
- Why data analysts should choose stories over statistics - Sep 26, 2019.
Join the Crunch Data Conference in Budapest, Oct 16-18, with stellar speakers from companies like Facebook, Netflix and LinkedIn. Use the discount code ‘KDNuggets’ to save $100 off your conference ticket.
Budapest, Career Advice, Crunch Conference, Data Analytics, Data Science, Hungary, Storytelling
- The thin line between data science and data engineering - Sep 25, 2019.
Today, as companies have finally come to understand the value that data science can bring, more and more emphasis is being placed on the implementation of data science in production systems. And as these implementations have required models that can perform on larger and larger datasets in real-time, an awful lot of data science problems have become engineering problems.
Data Engineering, Data Science, Podcast
- Applying Data Science to Cybersecurity Network Attacks & Events - Sep 19, 2019.
Check out this detailed tutorial on applying data science to the cybersecurity domain, written by an individual with backgrounds in both fields.
Cybersecurity, Data Science, Machine Learning, Python, Security
- 5 Beginner Friendly Steps to Learn Machine Learning and Data Science with Python - Sep 19, 2019.
“I want to learn machine learning and artificial intelligence, where do I start?” Here.
Beginners, Data Science, Machine Learning, Python
- Version Control for Data Science: Tracking Machine Learning Models and Datasets - Sep 13, 2019.
I am a Git god, why do I need another version control system for Machine Learning Projects?
Data Science, Datasets, Machine Learning, Modeling, Version Control
There is No Free Lunch in Data Science - Sep 12, 2019.
There is no such thing as a free lunch in life or data science. Here, we'll explore some science philosophy and discuss the No Free Lunch theorems to find out what they mean for the field of data science.
Algorithms, Data Science, Machine Learning, Optimization
- The 5 Graph Algorithms That Data Scientists Should Know - Sep 10, 2019.
In this post, I am going to be talking about some of the most important graph algorithms you should know and how to implement them using Python.
Algorithms, Data Science, Data Scientist, Graph, Python
10 Great Python Resources for Aspiring Data Scientists - Sep 9, 2019.
This is a collection of 10 interesting resources in the form of articles and tutorials for the aspiring data scientist new to Python, meant to provide both insight and practical instruction when starting on your journey.
Data Science, Data Scientist, Programming, Python
- I wasn’t getting hired as a Data Scientist. So I sought data on who is. - Sep 6, 2019.
Instead of focusing on skills thought to be required of data scientists, we can look at what they have actually done before.
Career, Career Advice, Data Science, Data Science Skills, Data Scientist
- Automate your Python Scripts with Task Scheduler: Windows Task Scheduler to Scrape Alternative Data - Sep 3, 2019.
In this tutorial, you will learn how to run task scheduler to web scrape data from Lazada (eCommerce) website and dump it into SQLite RDBMS Database.
Data Science, Python, Web Scraping
- Top 10 Data Science Use Cases in Energy and Utilities - Sep 2, 2019.
In this article, we will consider the most vivid data science use cases in the industry of energy and utilities.
Data Science, Energy, Use Cases, Utilities
- Types of Bias in Machine Learning - Aug 29, 2019.
The sample data used for training has to be as close a representation of the real scenario as possible. There are many factors that can bias a sample from the beginning and those reasons differ from each domain (i.e. business, security, medical, education etc.)
Bias, Data Science, Data Scientist, Machine Learning
Top Handy SQL Features for Data Scientists - Aug 23, 2019.
Whenever we hear "data," the first thing that comes to mind is SQL! SQL comes with easy and quick to learn features to organize and retrieve data, as well as perform actions on it in order to gain useful insights.
Data Science, Data Scientist, SQL
