Last month, Vidora held ‘The Future of Machine Learning Business’ event in conjunction with News Corp. At the event, we discussed the future of the machine learning space. We also spoke about the latest innovations in the space. Finally, we discussed how media businesses such as News Corp think about ML and plan for its future.

Part One was a talk by Vidora CTO Abhik Majumdar, PhD. Abhik’s speech was about the future of machine Learning in business. In this clip, Abhik discusses how the future of machine learning is a single “master algorithm”. This master algorithm automates the entire machine learning pipeline.

The machine learning pipeline consists of a four-step process. As we go through the process, the ML engine processes raw, unstructured data and produces predictive models on the other end. The vast majority of the work lies in wrangling data into a suitable framework for machine learning. As a result, automating these steps is where we have spent a lot of time and energy at Vidora. Cortex, Vidora’s flagship product, uses automated machine learning techniques to give self-service machine learning to anyone in a business. As a result, this allows you to build and use machine learning models at scale with just a few clicks.

Step 1: Data Pre-processing

Cortex collects billions of raw data points (structured and unstructured) from multiple sources in real-time.

Step 2: Feature Cleaning

Next, cleaning data, removing outliers, accounting for missing features, normalizing input features, and merging multiple sources can be a painful and time-consuming process.

Step 3: Feature Engineering

Cortex then uses its experience with global Fortune 500s to transform raw data into complex features which maximize the predictive power of your models. Transformations include time quantization, sequence generation, uncommon data removal, summation of categorical events, and others.

Step 4: Model Selection

Finally, Cortex constantly trains, tests, and validates thousands of models, including state-of-the-art deep neural networks and gradient-boosted decision trees. After doing so, Cortex evaluates the performance of each model and selects the winner on an ongoing basis. Cortex’s predictive platform adapts in real-time to ongoing data as it’s ingested, constantly learning and adapting to optimize for your strategic business goals.

At Vidora, we believe that in the future these steps will be increasingly automated, making machine learning, faster, more powerful and more accessible than ever before.

Click here to see a segment from Abhik’s speech about the Future of ML, and reach out to us at to learn more!

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