The research and development ( R&D) phase of building an AI model to address a business problem is characterized by rapid exploration and iteration. Everything is on the table and experimentation is encouraged, from understanding how to frame the problem, to determining how to most effectively use the data on hand, to discovering the model architecture with the best performance.

Welcome to the second installment of our ModelOps blog series, where we dive deep into the next step in the ModelOps pipeline, Model Training.

During Model Training, we feed large volumes of data to our model so it can learn to perform a certain task very well. This blog follows the first post in our series where we cover everything you need to know about Data Acquisition and Preparation and discuss how foundational it is for successful Artificial Intelligence (AI) investments. If you missed it, check as a great lead-in to this post.

Containers. Microservices. Kubernetes. Where to begin?

Containers & Microservices are the heart of our secure ModelOps Platform to discover, deploy, manage & govern machine learning at scale

Containers and Microservices have become the most popular way for new software deployments, and for application re-factoring, such as twelve factor apps.

At Modzy, we use containers and Kubernetes for our entire platform. …

Representation of training data imbalance. Modzy ModelOps AI Platform  for machine learning at scale

Data imbalance, or imbalanced classes, is a common problem in machine learning classification where the training dataset contains a disproportionate ratio of samples in each class. Examples of real-world scenarios that suffer from class imbalance include threat detection, medical diagnosis, and spam filtering.

Class imbalance can make training efficient machine…

Representation of Modzy, the secure ModelOps Platform to discover, deploy, manage & govern machine learning at scale
Train Hard — Time to talk about training data security

The effectiveness and predictive power of machine learning models is highly dependent on the quality of data used during the training phase. In most real-world scenarios, models are trained using domain specific data provided by known and trusted sources. …

Representation of Modzy, the secure ModelOps Platform to discover, deploy, manage & govern machine learning at scale
ModelOps approach to discover, deploy, manage & govern machine learning at scale

Only about half of all machine learning models actually get deployed. Far fewer produce real value. Many early adopters have invested millions, but remain unimpressed and discouraged by the lack of returns thus far. For most organizations, getting “out of the lab” and into “production” is too hard and costly.

Modzy ModelOps AI Platform transfer learning image racecar

In simple terms, transfer learning is a machine learning approach where a model that is already trained on a specific data set and developed for a specific task is reused as the starting point for training on a different data set for a different task. Transfer learning is a popular…

Josh Sullivan

Author, Entrepreneur and business leader. Machine Learning @ Modzy

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