Commentary & News
Members of machineByte receive daily news & commentary, authored by the machineByte editorial team, on the latest trends, innovations and issues in machine learning, data science, blockchain and related markets. The news and commentary are delivered through the lenses of quantitative professionals, investment managers, machine learning professionals and data scientists at the leading investment banks, hedge funds, institutional investors, technology providers and big data companies. The commentary & news platform is structured across asset classes, markets, types of learning and ecosystems.
Join senior machine learning, data science and asset allocation professionals from firms such as GSAM, Citadel, BlackRock, PIMCO, J.P.Morgan Asset Management, World Bank, AXA IM, OPTrust, Neuberger Berman and others at machineByte conferences around the globe. Our educational seminars provide training on python for finance, natural language processing for portfolio construction and reinforcement learning for investment management, among other topics. Access to presentations and content delivered at machineByte events is only open to machineByte members.
machineByte’s industry & academic ThinkTanks in London, New York & Hong Kong bring together the leading quantitative, data science and machine learning professionals in finance and tech to discuss the latest trends and innovations in machine learning in finance.
Data & Research
Our unique research and data provides analysis in to how institutional investors are applying machine learning across markets, asset classes and products. The research and data will also cover where investors are using alternative data and with which providers, where they are looking to grow their application of machine learning and the challenges they face when it comes to areas such as deep learning and big data in portfolio construction, allocation frameworks, trading, portfolio management and analysis/modelling. We will also offer bespoke research that will identify non-linear trends through the application of data science techniques in quantitative investing markets. For further information, please email research@machineByte.com.
The Journal of Machine Learning in Finance
machineByte’s journal delivers academic and practitioner insights from quantitative finance, data science and tech innovators with one clear goal: providing a platform that fosters education and innovation in machine learning and alternative data through independent research. Call for submissions to the Editorial Board will be announced on Jan. 18, 2019, with deadline for submissions March 15, 2019. The bi-annual Journal of Machine in Learning in Finance is included in your machineByte membership. For further information, please email journal@machineByte.com.
machineByte’s podcasts and webinars will feature distinguished machine learning and data science professionals presenting on areas across programming, types of learning and generating alpha through machine learning, among other areas. Our techByte, dataByte, quantByte and academicByte channels will profile thoughtleaders in machine learning and alternative data, while the soon-to-be-launched soundByte podcast series will cover the latest trends, developments and challenges in machine learning in finance and related industries. Access to machineByte’s media platform is available to members only. To get a free trial, please email info@machineByte.com.
We want to hear from you.
For content or all other machineByte platform questions, please contact Chantal Hermans at chantal@machineByte.com in London.
For membership / sponsorship questions, please contact Chas Reese at firstname.lastname@example.org in Boston.
For questions related to our research, please contact Patrick Fay at email@example.com.