The Programmer Myth of Data Science
If you’re thinking of hiring a computer programmer as your data scientist, you may want to back up. While the two careers have a lot in common – writing programs, working with sophisticated machines, creating products that provide business value – putting “programmer” on your job description and hoping... Read more
What is an AI Engineer?
AI is coming for your business, and at the most recent ODSC East keynote, Michael Stonebraker of MIT and Tamr laid it all out for us. If you aren’t ready to hire the experts, you won’t be ready. AI Engineers are going to be the next biggest thing because... Read more
Watch: Challenges and Opportunities in Applying Machine Learning
There are many opportunities in applying machine learning, whether as an individual developer or in a business. But how do you get started? This talk provides an overview that separates fact from fiction and proposes processes to find opportunities for applying ML. This includes understanding where ML can have... Read more
5 Ways AI Can Upgrade Your eCommerce Business
The eCommerce sector is one of the most profitable ones, with millions of online stores and digital portals showcasing products meant to cater to you from head to toe. According to Statista, the eCommerce revenues worldwide is anticipated to grow to 4.88 trillion US dollars in 2021. Clearly, the... Read more
Watch: Deploying Investments in AI and Machine Learning
Over the next 18 months, companies will be completing the R&D phase of their AI/ML investments and will be deploying their models and algorithms to production. The proper execution of deploying your AI/ML models will separate the organizations who see an ROI on AI from those who don’t. This... Read more
Operationalization of Machine Learning Models
Lots of businesses want to use machine learning, but few are ready to integrate machine learning into a real-life context of operations. Dr. Mufajjul Ali, Data Solutions Architect for Microsoft, outlines how Microsoft is addressing these needs and offers some advice for businesses looking to operationalize ML models and... Read more
What are MLOps and Why Does it Matter?
During the industrial revolution, the rise of physical machines required organizations to systematize, forming factories, assembly lines, and everything we know about automated manufacturing. During the first tech boom, Agile systems helped organizations operationalize the product lifecycle, paving the way for continuous innovation by clearing waste and automating processes... Read more
9 Common Mistakes That Lead To Data Bias
Data scientists spend a lot of time with data, which by itself is neutral. It only follows that answers gleaned from the data would be neutral too. Even though data is neutral, our responses to data are sometimes filled with bias that can skew our outcomes. Let’s examine some... Read more
How to Choose Machine Learning or Deep Learning for Your Business
AI is the future, or so you’re hearing. Every day, news of another organization leveraging AI to produce business outcomes that outstrip competition hit your inbox, but your company either hasn’t started at all or is mired in the discussion. AI, machine learning, and deep learning are sometimes used... Read more
Why You Still Need Business Intuition in the Era of Big Data
Artificial intelligence is coming for your job, right? Not so fast. Despite what doomsday enthusiasts predict, machines are a long way off from becoming dangerously sentient. Instead, machines are taking over areas where humans just aren’t that great, freeing up human labor to do what we do best, create,... Read more