Data Scientist Information Technology

Ngo Hoang Phuc

093-***-**** • ads61c@r.postjobfree.com • 21/02/1998

***/** ** **** ***** St • Dist 10 HCMC

linkedin.com/in/phucnh-hcm-in

Summary

Aiming at working as a data scientist, my recent goal is to get a job that gives me chances of interacting with real- life projects, working with experienced members and enhancing skills of using assisting tools. My greatest strengths are being progressive, flexible, dedicated to duties, and willing to help others. Core Competencies

• Statistics foundation

• Programming foundation

• Big data foundation

• Data preparation

• Data visualization

• Model building

• Problem definition

• Researching

Technical Skills

• Mathematics: Linear Algebra, Calculus, Probability, Statistics

• Programming languages: Python, Java, C++

• Machine learning libraries: NumPy, Scikit-Learn, Pandas, TensorFlow, Keras, Matplotlib, Scrapy, Beautiful Soup, Seaborn, OpenCV, nltk

• Database management system: PostgreSQL, MySQL

• Big data platform: Spark, Hadoop

• Software frameworks: React Native, .NET, Django, Android’s Java API

• Other tools: Git, docker

Foundations

Machine learning

Machine Learning: A Probabilistic Perspective

• Good knowledge of mathematical foundations (including probability, statistics, linear algebra and calculus) for machine learning.

• Good knowledge of core concepts: (generalized) linear models, directed and undirected graph models, mixture models, Gaussian processes, adaptive basis function models, dimension reduction algorithms (factor analysers, PCA, SVD), support vector machines, gradient descent and Newton’s learning methods, EM-based algorithms, exact and variational inferences, solutions for common learning problems (numerical stability, missing data, regularization), Bayesian inference, Monte Carlo inference.

• Able to turn the mentioned concepts into Python code. Deep learning

• Good knowledge of the convolution operation, recurrent structures and implemented models derived from them.

• Good knowledge of optimization algorithms (i.e. adaptive learning rates, approximate second-order methods) and regularization techniques (i.e. data augmentation, early stopping, dropout). Experience

University of Information Technology 2021

Evaluating deep learning methods used in emotion recognition systems

• Identified three theoretical approaches for measuring human’s emotions, their advantages and disadvantages.

• Surveyed machine learning and deep learning methods for classifying facial expressions and evaluated their applicability in real-time systems based on accuracy, processing speed and possible improvements.

• Collected and examined two verified datasets including AffectNet and FER2013.

• Created a new dataset that lessons the class imbalance problem existing in FER2013.

• Adapted and built naive GoogleNet, ResNet and Inception models based on their original research papers.

• Upgraded the ResNet model with Residual Unit and the Inception model with Factoring Convolution, grid reduction.

• Compared models in terms of the number of parameters, storage requirement, accuracy and processing speed.

• Integrated the upgraded Inception model, which has an accuracy of 65.97% and able to process more than 2500 images/minute, into a web-based system designed to assist employee management in small stores. Admicro 2020

Developing a word embedding library - Intern

• Collected articles belonging to ten or more categories on kenh14.vn, news.zing.vn, thanhnien.vn, tuoitre.vn, vnexpress.net.

• Cleaned the collected data, standardized texts, eliminated special characters, stop words, and tokenized the result.

• Surveyed and compared machine learning word embedding methods applicable to Vietnamese.

• Built and compared the word2vec, GloVe, fastText models after trained with preprocessed data. University of Information Technology 2020

Developing a replica of the game Gimmick! with C++

• Collected sprites of the playable character, enemies, tilesets.

• Examined the two first rounds and the final round, determined basic states and moving mechanisms of objects.

• Designed a set of classes and their relations based on the object-oriented programming approach.

• Implemented and adjusted the collision algorithm, the grid-based scene management mechanism, resource management flow and a control mechanism.

• Implemented and adjusted class designs.

Accomplishments

• IELTS certificate (band score: 7.0)

• First place in provincial excellent student contests in Physics

• Silver and Bronze medals in Physics at April 30th traditional Olympic competitions

• Attending national excellent student contests

Education

University of Information Technology April 2022

Degree of engineer – Software engineering

• GPA 3.00

Additional Information

• Personal Interests: traveling, badminton, boardgames

• Volunteer: CleanUp Vietnam – Member (2017), Spring Volunteer Campaign – Organizer (2019), UIT Job Fair – Member (2019)

• Skills: active listening, focus, ability to grasp the big picture

Contact this candidate