Overcoming Challenges in Machine Learning Model Training
Summary
To conclude this blog series, this post will highlight challenges faced when building machine learning models and offer tips and tricks for overcoming those roadblocks. And if you’re looking to the cloud as a solution, that could be a costly answer because machine learning models run for a long time and consume a lot of GPU resources. Today, machine learning is more widely available and easier to access — even for nontechnical folks — than it’s ever been thanks to APIs provided by tech companies like Amazon. But that availability and ease of access means people are likely to use machine learning without fully understanding it, which could lead to trouble if they start making business decisions based on their results. At Cardinal Peak, we uniquely understand machine learning and have employed it across a number of projects, from Bluetooth headphones with active noise cancellation and mobile apps to video streaming and medical test diagnosis.