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Chris Kachris
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  • Wilmington, DE
  • United States
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Chris Kachris posted a blog post

Run 100x faster your Scikit-learn ML apps: A use case on Naive Bayes

Scikit-learn (also known as sklearn) is a widely used free software machine learning library for the Python programming language. It has been adopted by many companies and universities as it features various classification, regression and clustering algorithms including support vector machines, random forests, gradient boosting, and k-means. SKlearn is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy.Scikit-learn is largely written in Python and uses…See More
Mar 1
Chris Kachris's blog post was featured

Performance evaluation of cloud computing platforms for Machine Learning

A use case on Logistic regression trainingOver the last few years there are several efforts for more powerful computing platforms to face the challenges imposed by emerging applications like machine learning. General purpose CPUs have been developed specialized ML modules, GPUs and FPGAs with specialized engines are around the corner. Several startups develop novel ASICs specialized for ML applications and Deep Neural networks.In this article we perform a comparison of 3 different platforms…See More
Dec 12, 2019
Chris Kachris posted a blog post

Accelerating data science and HPC applications with FPGAs using Jupyter Hub, instantly.

Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more.Due to its simplicity it has gained wide popularity among the data scientists and the HPC users that want to create and share applications that integrates the code, the comments and the…See More
Nov 14, 2019
Chris Kachris and Rohan Kotwani are now friends
Nov 11, 2019
Chris Kachris posted a blog post

Open-source Logistic Regression FPGA core for accelerated Machine Learning

Machine learning algorithms are extremely computationally intensive and time consuming when they must be trained on large amounts of data. Typical processors are not optimized for machine learning applications and therefore offer limited performance. Therefore, both academia an industry is focused on the development of specialized architectures for the efficient acceleration of machine learning applications.FPGAs are programmable chips that can be configured with tailored-made architectures…See More
Jul 3, 2019
Chris Kachris's blog post was featured

Open-source Logistic Regression FPGA core for accelerated Machine Learning

Machine learning algorithms are extremely computationally intensive and time consuming when they must be trained on large amounts of data. Typical processors are not optimized for machine learning applications and therefore offer limited performance. Therefore, both academia an industry is focused on the development of specialized architectures for the efficient acceleration of machine learning applications.FPGAs are programmable chips that can be configured with tailored-made architectures…See More
Jul 3, 2019
Chris Kachris posted a blog post

How to make ML engineers 5x more efficient

Emerging applications like machine learning (ML), big data analytics, and artificial intelligence (AI) has created the need for many companies to hire highly skilled and experienced work force. Demand for data scientists, ML engineers and data engineers is booming and will only increase in the next years. The January report from Indeed, one of the top job sites, showed a 29% increase in demand for data scientists year over year and a 344% increase since 2013.Salaries and OpExAt the same time…See More
May 19, 2019
Chris Kachris's blog post was featured

How to make ML engineers 5x more efficient

Emerging applications like machine learning (ML), big data analytics, and artificial intelligence (AI) has created the need for many companies to hire highly skilled and experienced work force. Demand for data scientists, ML engineers and data engineers is booming and will only increase in the next years. The January report from Indeed, one of the top job sites, showed a 29% increase in demand for data scientists year over year and a 344% increase since 2013.Salaries and OpExAt the same time…See More
May 19, 2019
Chris Kachris posted a blog post

How to save over $200k on your next machine learning project

Machine learning applications require powerful and scalable computing systems that can sustain the high computation complexity of these applications. Companies that are working on the domain of machine learning have to allocate a significant amount of their budget for the OpEx of machine learning applications whether this is done on cloud or on-prem.Typical machine learning application (especially when auto ML is used) can scale to as much as 30 nodes or higher (servers) to provide useful…See More
May 16, 2019
Chris Kachris's blog post was featured

How to save over $200k on your next machine learning project

Machine learning applications require powerful and scalable computing systems that can sustain the high computation complexity of these applications. Companies that are working on the domain of machine learning have to allocate a significant amount of their budget for the OpEx of machine learning applications whether this is done on cloud or on-prem.Typical machine learning application (especially when auto ML is used) can scale to as much as 30 nodes or higher (servers) to provide useful…See More
May 16, 2019

Profile Information

Short Bio
Chris Kachris is the CEO and co-founder of InAccel, Inc. InAccel helps companies speedup their ML applications on the cloud using FPGA-based accelerators.
My Web Site Or LinkedIn Profile
http://www.linkedin.com/in/kachris/
Field of Expertise
Data Science, Machine Learning
Professional Status
C-Level
Years of Experience:
10
Your Company:
InAccel
Industry:
Machine learning
Your Job Title:
CEO
Interests:
Contributing, Networking, New venture

Chris Kachris's Blog

Run 100x faster your Scikit-learn ML apps: A use case on Naive Bayes

Posted on February 25, 2020 at 2:00am 0 Comments

Scikit-learn (also known as sklearn) is a widely used free software machine learning library for the Python programming language. It has been adopted by many companies and universities as it features various classification, regression and clustering algorithms including support vector machines, random forests, gradient boosting, and k-means. SKlearn is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy.

Scikit-learn is largely written in Python…

Continue

Performance evaluation of cloud computing platforms for Machine Learning

Posted on December 12, 2019 at 4:30am 0 Comments

A use case on Logistic regression training

Over the last few years there are several efforts for more powerful computing platforms to face the challenges imposed by emerging applications like machine learning. General purpose CPUs have been developed specialized ML modules, GPUs and FPGAs with specialized engines are…

Continue

Accelerating data science and HPC applications with FPGAs using Jupyter Hub, instantly.

Posted on November 11, 2019 at 12:30am 0 Comments

Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more.

Due to its simplicity it has gained wide popularity among the data scientists and the HPC users that want to create and share applications that integrates the code, the…

Continue

Open-source Logistic Regression FPGA core for accelerated Machine Learning

Posted on July 1, 2019 at 10:00pm 0 Comments

Machine learning algorithms are extremely computationally intensive and time consuming when they must be trained on large amounts of data. Typical processors are not optimized for machine learning applications and therefore offer limited performance. Therefore, both academia an industry is focused on the development of specialized architectures for the efficient acceleration of machine learning applications.

FPGAs are programmable chips that can be configured with tailored-made…

Continue

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