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Wallaroo Labs Inc., an innovator in machine learning technology, has just secured a $25 million Series A funding from Microsoft’s M12, the venture arm of Microsoft Corp. The funding will be used to build out Wallaroo’s powerful machine learning platform and to hire more talent.

Wallaroo Labs, Inc., founded in 2017, is a privately held software company based in San Francisco, California, that offers an ML platform for companies to quickly and easily build and deploy ML models. This funding round is a testament to the innovative technology Wallaroo provides and its idea of making ML accessible and easier.

Overview of Wallaroo Labs

Wallaroo Labs is a machine learning platform that enables businesses to quickly build and deploy predictive models with machine learning technology. It is designed to eliminate the burden of managing complex data and provides an easy-to-use API for automatically building and deploying models. With Wallaroo Labs, businesses don’t need to be experts in data science or machine learning to create powerful predictive models. In addition, the platform provides users with real-time feedback on model accuracy, allowing them to quickly improve the accuracy of their models with data from any source without having to manage complex infrastructure.

Wallaroo Labs’ platform incorporates a range of technologies, including natural language processing (NLP), computer vision (CV), speech recognition (SR), supervised machine learning algorithms, unsupervised machine learning algorithms, and reinforcement learning. It also features semi-automated feature engineering capabilities for automatically detecting patterns in raw data and transforming them into features that can be used for better prediction results. The platform’s intuitive user interface helps users make changes quickly without needing any deep technical knowledge or expertise in data science or machine learning. Additionally, Wallaroo Labs provides advanced analytics tools like anomaly detection, multi-model recommendation systems, regression analysis, time series forecasting, and clustering techniques.

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Microsoft’s M12 Invests in Wallaroo Labs

Wallaroo Labs, a venture-backed startup based in San Francisco, is excited to announce that Microsoft’s M12 venture fund has invested in the company’s machine learning platform. The investment will further Wallaroo Labs mission to make machine learning accessible and easy for everyone.

Wallaroo Labs was founded in 2015 by CEO Joe DeBock and co-founders Sean Stephens, Nathan Goodman, and Michael Matiasz. The team comprises individuals with experience from Google Brain, Apple, Microsoft Research AI, Salesforce Einstein, Uber ATG, Twitter Cortex and other top ML teams in the industry.

The machine learning platform developed by Wallaroo Labs provides an end-to-end solution for Enterprises of all sizes ranging from startups to Fortune 500 companies. The platform allows users to quickly build models with interactive drag-and-drop interfaces and make real time predictions on streaming data sources. It also provides integration capabilities with popular software ecosystems such as AWS SageMaker and Google Cloud ML Engine and open source platforms such as TensorFlow and H2O.ai.

By leveraging scalable architecture powered by emerging GPU technologies such as NVIDIA CUDA the Wallaroo platform can handle workloads up to 100x faster than alternative solutions. This makes it ideal for supporting time sensitive applications such as fraud detection or smart building analytics where latency is critical for achieving accurate results at scale on streaming data sources like IoT devices or security cameras.

With its new funding from M12 Wallaroo Labs plans to grow its engineering team along with product development initiatives to better serve its enterprise customer base while further innovating on its core offering of providing open source based enterprise grade machine learning solutions.

Wallaroo Labs’ Machine Learning Platform

Wallaroo Labs is an innovative machine learning platform that seeks to provide businesses with powerful tools to make better decisions faster. The platform recently secured a $25M Series A Round of funding from Microsoft’s M12 Venture Fund. This investment indicates that machine learning is powerful, profitable, and ready to mainstream.

In this article, we’ll explore how Wallaroo Labs’ machine learning platform differs from the competition and why it is so attractive to enterprises.

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Machine Learning Platform Overview

Wallaroo Labs provides a powerful and versatile machine learning platform. Wallaroo’s platform has the necessary tools to build ML-driven applications or use more advanced techniques like deep learning. With a wide range of features and plugins, Wallaroo simplifies and accelerates your projects while ensuring clean separation between different stages of development. Let’s take a closer look at what the Wallaroo ML Platform offers.

The Platform can be deployed on major cloud platforms such as AWS and Azure, with easy integration with other services like Apache Spark and Kinesis. This means that your existing investments in data lakes, analytics tools etc., can be easily brought in line with the new model. Wallaroo also integrates well with Python for data scientists already familiar with Python frameworks such as TensorFlow, Keras or Scikit Learn. As an added benefit, the platform supports big data analysis framework Apache Mahout, which can help improve model performance by leveraging huge datasets to mathematically define relationships in data sets up to orders of magnitude larger than what’s possible using traditional processing models using just single machines.

Additionally, Wallaroo has built-in workflow orchestration capabilities which allow users to manage the entire ML lifecycle from training models to deployment along with monitoring performance metrics such as accuracy or efficiency across different versions in an automated way, allowing for much faster turnaround times when dealing with multiple versions of any given model. This process is made all the easier by unified APIs that enable users to stay agile throughout development iterations — irrespective of whether they work on batch processing jobs or real time predictions — ensuring developers spend less time debugging instead on creating better models faster.

With its comprehensive and versatile set of features, Wallaroo Labs’ machine learning platform makes it easy for developers to build professional-grade ML applications quickly and efficiently— providing immense power that would otherwise require specialised skill sets, domain expertise — accelerating development cycles significantly while enabling higher quality projections over larger datasets than ever before!

Wallaroo Labs’ Machine Learning Platform Features

Wallaroo Labs’ Machine Learning Platform offers several features which make it useful to organisations looking to expand their machine learning capabilities. It has been designed to be easily integratable with existing systems, and can be used as a stand-alone platform. With its built-in scalability and fault tolerance, the Wallaroo Labs’ platform is perfect for creating and deploying highly reliable applications with minimal effort.

The main features offered by the Wallaroo Labs’ Machine Learning Platform include:

-Scalability: Wallaroo Labs’ Machine Learning Platform supports a wide range of workflows, even at enterprise scale. It includes built-in scaling capabilities that enable users to easily increase or decrease their processing demands depending on changing business needs.

-Real-Time Results: The platform processes data quickly and efficiently in real time, providing up-to-date results as inputs are received. This ensures continuous monitoring of key performance indicators (KPIs) is possible without requiring additional hardware investment or manual tasking.

-Automated Model Building & Deployment: The Wallaroo Labs’ Machine Learning Platform provides automated model building tools, along with an intuitive deployment process which simplifies the process for making applications available for use among various stakeholders or within teams that span multiple departments.

Furthermore, it features out-of-the-box support for major machine learning frameworks such as TensorFlow, Keras and Scikit Learn, allowing users to quickly create models in any environment without needing additional dependencies or libraries installed on their system. This allows developers to quickly explore ideas or iterate upon existing models with reduced overhead costs from setup or installation requirements, expediting the entire ML model development cycle from ideation to validation and deployment much faster than possible.

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Machine Learning Innovator Wallaroo Wins Backing from Microsoft’s M12 in $25M Series A Round

Wallaroo Labs, a machine learning innovator, recently announced a $25M Series A round of funding led by M12, Microsoft’s venture fund. This investment will further their mission to create a world-class machine learning platform, enabling organisations to easily build, deploy and scale their ML-enabled applications.

This article will discuss the benefits of Wallaroo Labs’ machine learning platform.

Cost Savings

Wallaroo Labs’ Machine Learning Platform can deliver significant cost savings to your business. Hosting the machine learning algorithm on a single server means you don’t need to purchase or pay for additional infrastructure support. This value proposition is attractive for companies looking for quick reinvestment in their existing systems and workflows. Furthermore, Wallaroo supports multiple language integrations that make it easy to use the same platform across many use cases.

With Wallaroo’s cost-saving features also come a variety of other benefits. Those include increased scalability, faster time-to-market, automated model retraining and testing, and access to real-time analytics and insights. For example, this solution allows users to quickly generate useful data models with high accuracy levels quickly—importing your data from sources such as distributed databases or text files can further speed up the process. Additionally, you can use the platform’s integrated tools and APIs to customise settings or modify existing models or algorithms anytime during the development process. More importantly, its efficient model retraining keeps your production system up-to-date with new data, allowing for more accurate usage predictions for machine learning solutions deployed in production settings.

Increased Efficiency

Using Wallaroo Labs’ machine learning platform, organisations can realise significant efficiency and cost containment gains. The platform provides robust automation and scalability that help reduce human effort while increasing accuracy. In addition, it enables organisations to rapidly build and deploy sophisticated machine learning models using framework-agnostic, customizable libraries. This helps reduce the time required to train models and the effort required to troubleshoot, validate and optimise configurations over time.

The platform also offers powerful tools for preprocessing data such as feature engineering, data cleansing and normalisation. This allows for more effective analysing of complex datasets. Additionally, it can be used to monitor model performance in real-time, providing feedback that can be used to continually optimise models for better results.

Wallaroo Lab’s machine learning platform enables organisations to confidently identify unknown patterns to gain meaningful insights from available data sets. In addition, it is optimised for rapid deployment with minimal upfront investment, allowing organisations to focus their resources on business outcomes instead of platform architecture or maintenance costs. The ability to quickly gain insights from large data sets makes it possible for businesses of any size to leverage the power of AI without large upfront investments or lengthy implementation cycles – resulting in increased efficiency overall.


Bella Riley

Born at the dawn of the digital age, Bella swiftly recognized the potential of blockchain technology to revolutionize... well, everything. With a background in computer science and a heart that beats in code, Bella ventured into the cryptoverse, where they found a passion for demystifying the complexities of cryptocurrencies for the masses.
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