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Avatar of 黃季承.
Avatar of 黃季承.
Past
後端工程師 & DevOps @創業家兄弟Kuobrothers Corp.
2022 ~ 2024
Senior Backend Engineer | DevOps | SRE
Dans 1 mois
黃季承 Backend Developer | DevOps [email protected]我從事 5 年的電商後端開發與 1 年的 DevOps 維運,並參與超過 4 年的 Scrum 敏捷開發。後端主要負責產品功能研發、後台系統開發與既有服務重構。曾參與生活市集即享券開發,負責與合作夥伴釐清事項、跟 PM 討論整合方式、設
AWS
CI/CD Drone
Cloudflare
Sans Emploi
Prêt à l'interview
Temps plein / Intéressé par le travail à distance
4 à 6 ans
National Taipei University of Technology
資工系
Avatar of 李佳謙.
Avatar of 李佳謙.
Past
Marketing Manager @幫你優股份有限公司 BoniO Inc. / 閱讀優有限公司 TaaO Company Limited
2021 ~ Présent
Marketing Manager
Dans 1 mois
李佳謙 CHIEN LI Marketing Manager / BoniO Inc. Marketing Strategy | Customer Growth 負責品牌行銷,規劃產品銷售策略,推動品牌會員成長 熟悉市場、訂閱經濟、平台營運 以終為始策略型思考,帶領團隊有效達到營運目標 工作專長 用戶、營運成長數據指標分析 Operating Data Management ● 產品市場規模及用戶調
WordPress
Google Analytics
Project Management
Sans Emploi
Prêt à l'interview
Temps plein / Intéressé par le travail à distance
4 à 6 ans
淡江大學
英文學系
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Avatar of the user.
Past
資深前端工程師 @比房科技
2022 ~ 2024
Frontend developer.
Dans 1 mois
Frontend
Backend
Product
Sans Emploi
Prêt à l'interview
Temps plein / Intéressé par le travail à distance
4 à 6 ans
暨南大學
電機工程
Avatar of the user.
Avatar of the user.
行銷副理 / KOL Radar 行銷科技事業部 @愛卡拉互動媒體股份有限公司
2021 ~ Présent
品牌專案企劃、網路行銷企劃、數位行銷企劃
Dans 1 mois
Google Analytics
Sales & Marketing
Photoshop
Employé
Prêt à l'interview
Temps plein / Intéressé par le travail à distance
4 à 6 ans
臺北市立大學
英語教學系
Avatar of the user.
Avatar of the user.
智慧製造全端開發工程師 @聯華電子股份有限公司
2022 ~ Présent
AI工程師、機器學習工程師、深度學習工程師、影像演算法工程師、資料科學家、Machine Learning Engineer、Deep Learning Engineer、Data Scientist
Dans 1 mois
Python
Qt
Git
Employé
Prêt à l'interview
Temps plein / Intéressé par le travail à distance
4 à 6 ans
元智大學
工業工程與管理學系所
Avatar of Sosuke Guo.
Avatar of Sosuke Guo.
Past
資深前端工程師 @辰凝有限公司
2022 ~ 2023
前端工程師 Front-End Developer
Dans 1 mois
Sosuke Guo 專職於網頁前端工程師近五年,擅於從0開始打造產品,有用Vue + Golang + Python自己打造產品的經驗。 前端工程師 Front-End Developer [email protected] 作品 - SocialPicMaker.com 製作精美Twtter card 的小工具網站 只要兩個步驟,輸入網址、點擊下載,即可完成 可以選擇黑白兩種介面佈
vue.js
golang
Python
Sans Emploi
Prêt à l'interview
Temps plein / Intéressé par le travail à distance
4 à 6 ans
Avatar of Patrick Hsu.
Avatar of Patrick Hsu.
Algorithm Research & Development @適着三維科技股份有限公司 TG3D Studio Inc.
2021 ~ Présent
Software Engineer
Dans 1 mois
Patrick Hsu AI Research & Development As a seasoned AI engineer with six years of experience, I specialize in computer vision, 3D body model reconstruction, generative AI, and possessing some knowledge in natural language processing (NLP). | New Taipei City, [email protected] Work Experience (6 years) Algorithm Research & Design• TG3D Studio MayPresent A skilled engineer specialized in computer vision and generative AI with experience in developing and training AI models for digital fashion applications. Body AI: Virtual Try On Integrated cutting-edge technologies such as Stable Diffusion, ControlNet, and Prompt Engineering to create a sophisticated system for
Python
AI & Machine Learning
Image Processing
Employé
Prêt à l'interview
Temps plein / Intéressé par le travail à distance
4 à 6 ans
國立台灣大學
生物產業機電工程所
Avatar of Jimmy Lu.
Avatar of Jimmy Lu.
Past
Lead of Country Product Manager @Asus 華碩電腦股份有限公司
2022 ~ 2023
Business Development / Product Manager / Product Marketing/ Strategy Manager
Dans 1 mois
Jimmy Lu (呂正彥) Senior Product Manager [Consumer Electronics Expatriate PM/Sales/BD] Entrepreneurship business development & management Leadership flexible & efficient international/cross-functional organizing Target-oriented project lead & SOP consolidation, product lifecycle management Begin with the end in mind Go-to-market execution Taipei, Taiwan < > London, UK https://www.linkedin.com/in/itsjimmy/ [email protected] Work experience Senior Product Manager [Consumer NB & Gaming ] • ASUSTeK Computer Indonesia JulDec 2023 | Jakarta, Indonesia Key responsibilities & Achievements - #business management #business development #team leading #cross-functional organizing
Business Development Project Management
Cross-Functional Project Management
Product Life Cycle Management
Sans Emploi
Prêt à l'interview
Temps plein / Intéressé par le travail à distance
4 à 6 ans
國立陽明交通大學(National Yang Ming Chiao Tung University)
Bachelor of management , Management of Transportation and Logistics
Avatar of Ryan Po-Hsuan Chang.
Avatar of Ryan Po-Hsuan Chang.
資深全端工程師 @誠諾工程技術股份有限公司
2023 ~ Présent
Front-End / Back-End / Full Stack Web Developer
Dans 1 mois
張栢瑄 Ryan Po-Hsuan Chang 已有五年開發經驗,擅長使用Vue + TypeScript 和Laravel 來建構網頁系統,另外也有React 和Python 的開發經驗。喜歡挑戰新事務,不怕踩坑和重構,持續精進自己的技術。 Kaohsiung City, Taiwan https://ryanxuan930.github.io/ [email protected]技能 Frontend Nuxt (Vue 3) Next (React) Pinia TypeScript Tailwind CSS SCSS PrimeVue Next UI Backend
Vue.js
JavaScript
Python
Employé
Prêt à l'interview
Temps plein / Uniquement Travail à distance
4 à 6 ans
國立中山大學 National Sun Yat-Sen University
人文暨科技跨領域學士學位學程
Avatar of 楊晟.
Avatar of 楊晟.
運維工程師 DevOps @愛盛娛樂科技有限公司
2019 ~ Présent
Java 軟體工程師
Dans 1 mois
楊晟 運維工程師 DevOps New Taipei City, Taiwan 喜歡尋找程式碼中更優雅的做法,熱衷找到更高效率、更優雅的解決方案。 喜歡尋找 Solution,討厭遷就 Workaround https://www.cakeresume.com/sam0324sam 工作經歷 運維工程師 DevOps • 愛盛娛樂科技有限公司 七月Present - 全遠端 - (作品集) 使用 Java Quarkus 開發 RESTful API 後
JAVA
JavaScript
MySQL
Employé
Prêt à l'interview
Temps plein / Uniquement Travail à distance
4 à 6 ans
National Kaohsiung First University of Science and Technology
電腦與通訊工程系

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Software Engineer
Logo of Jash Data Sciences.
Jash Data Sciences
2020 ~ Présent
Pune, Maharashtra, India
Professional Background
Statut Actuel
Progrès de la Recherche d'Emploi
Professions
Data Engineer
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Logiciel
Expérience Professionnelle
2 à 4 ans
Management
Compétences
python
Machine Learning
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tensorflow
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Job search preferences
Position Désirée
Machine Learning Engineer
Type d'emploi
Temps plein
Lieu Désiré
Travail à distance
Intéressé par le travail à distance
Freelance
Éducation
École
Pune Institute of Computer Technology, Pune
Spécialisation
Electronics and Telecommunication
Imprimer
Sa8svkgvup7bc65xi1jh

Shishir Joshi

Full Stack Data Scientist and self taught Machine Learning enthusiast with experience of CV, NLP, Deep Learning and backend development.


Pune IN
[email protected]

Ph. : +91 8554067867  |  +91 9405181761

Skills


Machine Learning

Transformers (BERT, DistillBERT),

LSTMs, CNNs, SVMs, KNN, Decision Trees, ULMFiT,

Transfer Learning, Deep Learning, Computer Vision,



APIs / Libraries

OpenCV, Tensorflow, Keras, PyTorch, Fast.ai, Huggingface,

Scikit-Learn, Pandas,

PySpark.


Development

Python, shell scripting, Java, SQL/PL-SQL, GIT, Django, Flask

AWS [ EC2, S3, SQS, RDS, Sagemaker ]


Work Experience

Data Scientist,

GlobalFoundries |  Mar 2021 ~ Present

: Predictive Maintenance Model of Semiconductor Etching Tools
  • Created multiple POCs for predictive maintenance of semiconductor mfg. tools based on Remaining Useful Life using existing tool sensors and yield data for the Singapore Facility.
  • XGBoost Regressor and Autoregressive LSTM models were developed for the same in AWS Sagemaker.
  • Deployed models on premises in shadow mode for validation on live data.
:  Probability of Failure analysis/ model on Etching Tools
  • Built Probability of Failure model using test wafer particle counts to predict tool's internal state.
  • Two part model is made of Wafer Particle (defect) Count Regressor (Linear Reg., RandomForest Reg., XGBoost Regressor were used for POCs) and Thresholded CDF of Negative Binomial distribution.
  • Used Maximum Likelihood Estimation to model tool state based on multiple internal sensors, semiconductor recipe information and control limit thresholds
  • MLE model used with Threshold CDF framework shows promising results in terms of extending tool uptime and predicting possible failures based on trends in defect measurement.

Kzsi9r1kvr5ny9cmod1h

Data Scientist,

Jash Data Sciences |  Feb 2020 ~ Feb 2021

: Document Similarity Semantic Search
  • Researched, created and served document level semantic similarity search engine for an AI based hiring tech startup.
  • Compared the performance of LSTM Seq2Seq based Autoencoder for language modeling task with DistilBERT model on custom evaluation metric based on semantic similarity.
  • Created complete backend API to serve the fine tuned DistilBERT model via Flask and Highly optimized document embedding.
  • Implemented Approximate Nearest Neighbor search using graph based HNSW clustering for near real time retrieval.
: Insurance Email Classification and document NER 
  • Created word embedding and keyword extraction based email classification model (Test Set F1 score: 0.85).
  • My model out performed ULMFiT model fine tuned for email classification on same dataset (ULMFiT Test Set F1 score: 0.72).
  • Worked on implementing DistilBERT based NER pipeline using Huggingface Transformers.
: Inhovate - Analytics platform focused on the hospitality industry
  • Automated complete ETL logic in Bash/Python.
  • Worked on Backend API in Django and wrote custom query builders to dynamically compose and execute complex queries beyond the scope of Django's ORM.
  • Created linux processes and cron jobs for ETL, web server with load balancing using HAProxy and Gunicorn.

Kzsi9r1kvr5ny9cmod1h

Software Engineer,

Larsen and Toubro Infotech, | Sep 2018 ~ Dec 2019
  • Development and extension of BRAINS core banking platform.
  • Implemented source code management functionality in-house, saving $25k yearly in licensing costs to outsourced system
  • Worked on pilot project for creation of defaulter classification using Gradient Boosted Decision Tree classifier in Scikit-Learn.
Company@2x

Projects (Computer Vision, NLP, etc.)

Click here for colab notebooks

Qualia
  • https://github/qualia
  • Online Real Time Semantic Search using Transformers and HNSW nearest neighbour search.
  • Can be fine tuned on specific datasets with custom tokenisation requirements.
  • Uses Sentence Transformers as embedding model and HNSWlib as approximate nearest neighbour search index based on cosine similarity.
  • The aim is to make it "Online" - to be able to add new documents in parallel with querying.


StackExchange Question tags extraction

  • https://colab/stx
  • Multilabel classification for tag extraction from Stackexchange questions.
  • Used transfer learning to fine tune ULMFiT Language model on dataset (83% language modeling accuracy),
  • Used beautifulsoup4 (bs4) and regex to clean text.
  • Created Multi-Label classifier using ULMFiT as embedding layer.
  • Achieved >93% accuracy on tag prediction.

Machine Learning Based Automatic Fruit Grading and Classification

  • Machine Learning Based Automatic Fruit Grading and Classification:Funded by the University of Pune.
  • Trained Inception V3 CNN model via transfer learning for detecting grade of fruits based on visual quality, skin texture, and pre-defined standards.
  • Used OpenCV for image preprocessing (cropping, segmentation and feature extraction for comparison of classification on SVM) Achieved ~90% accuracy on test set.

MobileNet v2.0 Transfer Learning on the Caltech101 Dataset with TF2.0:

  • Trained my custom CNN on the 101 categories of the Caltech101 dataset.
  • Prepared a tf.Data input pipeline, and compared performance with transfer-trained MobileNetv2.0 model.
  • My Model achieved ~98% accuracy while MobileNet achieved ~80%

Education

Savitribai Phule Pune University, Pune | 2015 ~ 2018

Bachelor of Engineering (B.E.) | Electronics and Telecommunication,
Graduated First Class with Distinction from
Pune Institute of Computer Technology (PICT), Pune


Resume
Profile
Sa8svkgvup7bc65xi1jh

Shishir Joshi

Full Stack Data Scientist and self taught Machine Learning enthusiast with experience of CV, NLP, Deep Learning and backend development.


Pune IN
[email protected]

Ph. : +91 8554067867  |  +91 9405181761

Skills


Machine Learning

Transformers (BERT, DistillBERT),

LSTMs, CNNs, SVMs, KNN, Decision Trees, ULMFiT,

Transfer Learning, Deep Learning, Computer Vision,



APIs / Libraries

OpenCV, Tensorflow, Keras, PyTorch, Fast.ai, Huggingface,

Scikit-Learn, Pandas,

PySpark.


Development

Python, shell scripting, Java, SQL/PL-SQL, GIT, Django, Flask

AWS [ EC2, S3, SQS, RDS, Sagemaker ]


Work Experience

Data Scientist,

GlobalFoundries |  Mar 2021 ~ Present

: Predictive Maintenance Model of Semiconductor Etching Tools
  • Created multiple POCs for predictive maintenance of semiconductor mfg. tools based on Remaining Useful Life using existing tool sensors and yield data for the Singapore Facility.
  • XGBoost Regressor and Autoregressive LSTM models were developed for the same in AWS Sagemaker.
  • Deployed models on premises in shadow mode for validation on live data.
:  Probability of Failure analysis/ model on Etching Tools
  • Built Probability of Failure model using test wafer particle counts to predict tool's internal state.
  • Two part model is made of Wafer Particle (defect) Count Regressor (Linear Reg., RandomForest Reg., XGBoost Regressor were used for POCs) and Thresholded CDF of Negative Binomial distribution.
  • Used Maximum Likelihood Estimation to model tool state based on multiple internal sensors, semiconductor recipe information and control limit thresholds
  • MLE model used with Threshold CDF framework shows promising results in terms of extending tool uptime and predicting possible failures based on trends in defect measurement.

Kzsi9r1kvr5ny9cmod1h

Data Scientist,

Jash Data Sciences |  Feb 2020 ~ Feb 2021

: Document Similarity Semantic Search
  • Researched, created and served document level semantic similarity search engine for an AI based hiring tech startup.
  • Compared the performance of LSTM Seq2Seq based Autoencoder for language modeling task with DistilBERT model on custom evaluation metric based on semantic similarity.
  • Created complete backend API to serve the fine tuned DistilBERT model via Flask and Highly optimized document embedding.
  • Implemented Approximate Nearest Neighbor search using graph based HNSW clustering for near real time retrieval.
: Insurance Email Classification and document NER 
  • Created word embedding and keyword extraction based email classification model (Test Set F1 score: 0.85).
  • My model out performed ULMFiT model fine tuned for email classification on same dataset (ULMFiT Test Set F1 score: 0.72).
  • Worked on implementing DistilBERT based NER pipeline using Huggingface Transformers.
: Inhovate - Analytics platform focused on the hospitality industry
  • Automated complete ETL logic in Bash/Python.
  • Worked on Backend API in Django and wrote custom query builders to dynamically compose and execute complex queries beyond the scope of Django's ORM.
  • Created linux processes and cron jobs for ETL, web server with load balancing using HAProxy and Gunicorn.

Kzsi9r1kvr5ny9cmod1h

Software Engineer,

Larsen and Toubro Infotech, | Sep 2018 ~ Dec 2019
  • Development and extension of BRAINS core banking platform.
  • Implemented source code management functionality in-house, saving $25k yearly in licensing costs to outsourced system
  • Worked on pilot project for creation of defaulter classification using Gradient Boosted Decision Tree classifier in Scikit-Learn.
Company@2x

Projects (Computer Vision, NLP, etc.)

Click here for colab notebooks

Qualia
  • https://github/qualia
  • Online Real Time Semantic Search using Transformers and HNSW nearest neighbour search.
  • Can be fine tuned on specific datasets with custom tokenisation requirements.
  • Uses Sentence Transformers as embedding model and HNSWlib as approximate nearest neighbour search index based on cosine similarity.
  • The aim is to make it "Online" - to be able to add new documents in parallel with querying.


StackExchange Question tags extraction

  • https://colab/stx
  • Multilabel classification for tag extraction from Stackexchange questions.
  • Used transfer learning to fine tune ULMFiT Language model on dataset (83% language modeling accuracy),
  • Used beautifulsoup4 (bs4) and regex to clean text.
  • Created Multi-Label classifier using ULMFiT as embedding layer.
  • Achieved >93% accuracy on tag prediction.

Machine Learning Based Automatic Fruit Grading and Classification

  • Machine Learning Based Automatic Fruit Grading and Classification:Funded by the University of Pune.
  • Trained Inception V3 CNN model via transfer learning for detecting grade of fruits based on visual quality, skin texture, and pre-defined standards.
  • Used OpenCV for image preprocessing (cropping, segmentation and feature extraction for comparison of classification on SVM) Achieved ~90% accuracy on test set.

MobileNet v2.0 Transfer Learning on the Caltech101 Dataset with TF2.0:

  • Trained my custom CNN on the 101 categories of the Caltech101 dataset.
  • Prepared a tf.Data input pipeline, and compared performance with transfer-trained MobileNetv2.0 model.
  • My Model achieved ~98% accuracy while MobileNet achieved ~80%

Education

Savitribai Phule Pune University, Pune | 2015 ~ 2018

Bachelor of Engineering (B.E.) | Electronics and Telecommunication,
Graduated First Class with Distinction from
Pune Institute of Computer Technology (PICT), Pune