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Mustafa Murat Paksoy

from San Francisco, CA
Age ~39
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Also known as:
Mustafa M Paksoy, Murat Mustafa, Murat Paksoy T
Phone and address:
25 Eugenia Ave, San Francisco, CA 94110
Related to:
Samuel J Lippincott, 20Arielle Fisher, 33Gregory Anderson, 37Adam R Anderson, 79Genevieve AndersonTommy Clay, 52
Connected to:
Ayca Paksoy, 45Ahmad F Paktiawal, 56Ceu PakukAlicja M Pakula, 76Jacob L Pakula, 33Jennifer L Pakula, 61Leonard E Pakula, 77Nick K Pakula, 58Zenta Z Pakulis, 50Melissa D Pakusch, 33

Mustafa Paksoy Phones & Addresses

  • 25 Eugenia Ave, San Francisco, CA 94110
  • 350 Union St, San Francisco, CA 94133 (415) 986-7910
  • Tomales, CA
  • Fairfax, CA
  • Margate City, NJ
  • Swarthmore, PA

Work

Company: Amplitude 2020 Position: Director of engineering

Education

Degree: Bachelors, Bachelor of Arts School / High School: Swarthmore College 2003 to 2007 Specialities: Computer Science, Philosophy

Skills

Java • Javascript • Python • Distributed Systems • Css • Software Design • Html • Cloud Computing • Lucene • C • Search Engine Technology • Git • Ruby • Agile Methodologies • Software Engineering • Analytics • Scalability • Management • Software Development • Linux • Lisp • Erlang • Saas

Languages

Turkish • English

Industries

Information Technology And Services

Resumes

Resumes

Mustafa Paksoy Photo 1

Director Of Engineering

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Location:
San Francisco, CA
Industry:
Information Technology And Services
Work:
Amplitude
Director of Engineering
Searchlight.ai
Engineering Coach
Beyond Pricing
Chief Technology Officer Coach
Clearbrain
Chief Technology Officer Coach
Professor Moose
Chief Technology Officer Coach and Interim Vice President of Engineering
Education:
Swarthmore College 2003 - 2007
Bachelors, Bachelor of Arts, Computer Science, Philosophy
Skills:
Java
Javascript
Python
Distributed Systems
Css
Software Design
Html
Cloud Computing
Lucene
C
Search Engine Technology
Git
Ruby
Agile Methodologies
Software Engineering
Analytics
Scalability
Management
Software Development
Linux
Lisp
Erlang
Saas
Languages:
Turkish
English

Publications

Us Patents

Computer Implemented Methods And Apparatus For Finding People In A Physical Environment

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US Patent:
20130254312, Sep 26, 2013
Filed:
Mar 25, 2013
Appl. No.:
13/850109
Inventors:
Mustafa Paksoy - San Francisco CA, US
Assignee:
salesforce.com, inc. - San Francisco CA
International Classification:
H04L 29/08
US Classification:
709206
Abstract:
Disclosed are methods, apparatus, systems, and computer readable storage media for finding people in a physical environment. A server receives data indicating a location and identifies events corresponding to the location. Event data is transmitted to a computing device. Attendees at a selected event are identified and transmitted to the computing device. The server can receive a message addressed to an attendee and store data regarding the attendee. In some implementations, attendees may be identified from content posted on a social network. Additionally, certain attendees or events may be emphasized.

Automated Machine Learning To Generate Recommendations For Websites Or Applications

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US Patent:
20220277205, Sep 1, 2022
Filed:
Feb 26, 2021
Appl. No.:
17/187737
Inventors:
- San Francisco CA, US
William Robert Pentney - San Francisco CA, US
Eric M Pollmann - Los Altos CA, US
Cynthia E Rogers - Boston MA, US
Mustafa Paksoy - San Francisco CA, US
Zachery Abe Miranda - San Francisco CA, US
Assignee:
Amplitude Inc. - San Francisco CA
International Classification:
G06N 5/04
G06N 20/00
G06N 5/02
Abstract:
Implementations described herein relate to methods, systems, and computer-readable media for automated generation and use of a machine learning (ML) model to provide recommendations. In some implementations, a method includes receiving a recommendation specification that includes a content type and an outcome identifier, and determining model parameters for a ML model based on the recommendation specification. The method further includes generating a historical user feature matrix (FM), generating a historical content feature matrix (FM), and transforming the historical user FM and the historical content FM into a suitable format for the ML model. The method further includes obtaining a target dataset that includes historical results for the outcome identifier for a plurality of pairs of user identifiers and content items of the content type. The method further includes training the ML model using supervised learning to generate a ranked list of content items for each user identifier.
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Mustafa Murat Paksoy from San Francisco, CA, age ~39 Get Report