Opinions, Interviews, Reports
We welcome guest blogs and opinions - see submission guidelines.
Latest:
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Let’s Admit It: We’re a Long Way from Using “Real Intelligence” in AI - Apr 19, 2018.
With the growth of AI systems and unstructured data, there is a need for an independent means of data curation, evaluation and measurement of output that does not depend on the natural language constructs of AI and creates a comparative method of how the data is processed. -
Presto for Data Scientists – SQL on anything - Apr 19, 2018.
Presto enables data scientists to run interactive SQL across multiple data sources. This open source engine supports querying anything, anywhere, and at large scale. -
Hedge Yourself From a Risky Data Science Job - Apr 18, 2018.
This article covers why it's important to consider all the factors when being hired as a data scientist. -
7 Books to Grasp Mathematical Foundations of Data Science and Machine Learning - Apr 17, 2018.
It is vital to have a good understanding of the mathematical foundations to be proficient with data science. With that in mind, here are seven books that can help. -
Role of IoT in Education - Apr 17, 2018.
In this article, I will discuss the significance of IoT and gain insights on why this technology is becoming an integral part of the daily learning and teaching methodologies. -
When Do We Trust Machines? - Apr 16, 2018.
We propose a framework of "trust heatmap", show how the trust in machines depends on two key elements: their error rate and the costs of mistakes, and examine the automation frontier. -
Key Algorithms and Statistical Models for Aspiring Data Scientists - Apr 16, 2018.
This article provides a summary of key algorithms and statistical techniques commonly used in industry, along with a short resource related to these techniques. -
Are High Level APIs Dumbing Down Machine Learning? - Apr 16, 2018.
Libraries like Keras simplify the construction of neural networks, but are they impeding on practitioners full understanding? Or are they simply useful (and inevitable) abstractions? -
Don’t learn Machine Learning in 24 hours - Apr 13, 2018.
When it comes to machine learning, there's no quick way of teaching yourself - you're in it for the long haul. -
Machine Learning Engineer, Data Scientist among the best US Jobs in 2018 - Apr 12, 2018.
Machine Learning Engineer, with avg. salary of $136K and Data Scientist, with avg. salary $133K are among the top US jobs in 2018, according to job site Indeed. -
Onboarding Your Machine Learning Program - Apr 12, 2018.
Machine Learning's popularity is continuing to grow and has engraved itself in pretty much every industry. This article contains lessons from a data scientist on how to unlock it's full potential. -
Ten Machine Learning Algorithms You Should Know to Become a Data Scientist - Apr 11, 2018.
It's important for data scientists to have a broad range of knowledge, keeping themselves updated with the latest trends. With that being said, we take a look at the top 10 machine learning algorithms every data scientist should know. -
Top 8 Free Must-Read Books on Deep Learning - Apr 10, 2018.
Deep Learning is the newest trend coming out of Machine Learning, but what exactly is it? And how do I learn more? With that in mind, here's a list of 8 free books on deep learning. -
The Cold Start Problem with AI - Apr 10, 2018.
Why companies struggle with implementing AI and how to overcome it. -
Where Analytics, Data Science, Machine Learning Were Applied: Trends and Analysis - Apr 9, 2018.
CRM/Consumer Analytics, Finance, and Banking are still the leading applications, but Health Care and Fraud Detection are gaining. Anti-spam, Manufacturing, and Social are the fastest growing sectors in 2017, while Oil / Gas / Energy and Social Networks analysis have declined. -
Why so many data scientists are leaving their jobs - Apr 9, 2018.
We look at some of the big challenges and frustrations that data scientists face on a regular basis. -
Build a Foundation that Supports AI and Machine Learning - Apr 6, 2018.
In an upcoming livestream on April 19, we’ll dig into how to build a foundation that supports AI and Machine Learning with industry experts and uncover what many companies are going through. -
Why Data Scientists Must Focus on Developing Product Sense - Apr 6, 2018.
Data Scientists should focus on developing product sense to move fast and systematically, create models that are relevant and to able to know when to stop. -
Are New Technologies Killing Their Ancestors? - Apr 6, 2018.
Are automatic feature learning models (e.g. CNN) killing their previous manually engineered models? This is an important question that is to be answered in this article. -
Data Science and the Art of Producing Entertainment at Netflix - Apr 5, 2018.
Each Netflix production is a logistical challenge that consumes and produces a vast amount of data. The tech giant is utilising this data to help them create new content and assist them at every stage, from pre-production to launching the show. -
What Does GDPR Mean for Machine Learning? - Apr 4, 2018.
This post investigates how the GDPR, which comes into force at the end of May, will effect machine learning. -
How Do I Get My First Data Science Job? - Apr 2, 2018.
Here are the steps you need to obtain your first job in data science, including details on how to create a good portfolio, key networking tips, getting the right education and managing expectations. -
A Day in the Life of a Data Scientist: Part 4 - Apr 2, 2018.
Interested in what a data scientist does on a typical day of work? Each data science role may be different, but these contributors have insight to help those interested in figuring out what a day in the life of a data scientist actually looks like.
March:
- Semantic Segmentation Models for Autonomous Vehicles
- Principles of Guided Analytics
- Comparing Deep Learning Frameworks: A Rosetta Stone Approach
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5 Things You Need to Know about Sentiment Analysis and Classification
We take a look at the important things you need to know about sentiment analysis, including social media, classification, evaluation metrics and how to visualise the results. - Data Skills: They’re Not Just for Data Scientists
- 8 Common Pitfalls That Can Ruin Your Prediction
- What Machine Learning Isn’t
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5 Things You Need to Know about Big Data
We take a look at five things you need to know about Big Data.
- Creating a simple text classifier using Google CoLaboratory
- So, How Many Machine Learning Models You Have NOT Built?
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Will GDPR Make Machine Learning Illegal?
Does GDPR require Machine Learning algorithms to explain their output? Probably not, but experts disagree and there is enough ambiguity to keep lawyers busy.
- KDnuggets – Favorite Data Science / Machine Learning Blog
- Hierarchical Classification – a useful approach for predicting thousands of possible categories
- How StockTwits Applies Social and Sentiment Data Science
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18 Inspiring Women In AI, Big Data, Data Science, Machine Learning
For the 2018 international women's day, we profile 18 inspiring women who lead the field in AI, Analytics, Big Data , Data science, and Machine Learning areas.
- Get ready for smart apps
- Great Data Scientists Don’t Just Think Outside the Box, They Redefine the Box
- Is an AI /machine-driven world better than a human driven world?
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The Two Sides of Getting a Job as a Data Scientist
Are you a Data Scientist looking for a Job? Are you a Recruiter looking for a Data Scientist? If you answered yes or NO to this questions you need to read this.
- Blockchains and APIs
- Should You Ever Volunteer Your Data Skills for Free?
- A Few Statistics Tips for Marketers
- Deep Misconceptions About Deep Learning
- How to Survive Your Data Science Interview
- Four Broken Systems & Four Tech Trends for 2018