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SFU Professional Computer Science

An unofficial publication by students of the master’s program in professional computer science

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XGBoost: A Deep Dive into Boosting

XGBoost: A Deep Dive into Boosting

Every day we hear about the breakthroughs in Artificial Intelligence. However, have you wondered what challenges it faces?

Feb 3, 2020

Recommendation Systems: Collaborative Filtering using Matrix Factorization — Simplified

Recommendation Systems: Collaborative Filtering using Matrix Factorization — Simplified

Matrix Factorization explained using understandable examples

SACHIN PRABHU THANDAPANI

Mar 1, 2019

An Introduction to Convolutional Neural Network (CNN)

An Introduction to Convolutional Neural Network (CNN)

cmpt733_dataproject

Feb 10

Detecting Malicious URLs

Detecting Malicious URLs

A comprehensive guide using ML and NLP Techniques

Feb 11

Hierarchical Time Series Forecast for Apparel Industry — Doppler Effect

Hierarchical Time Series Forecast for Apparel Industry — Doppler Effect

Developing a solution for the retail industry to get the sales forecast across space, time, and product dimension.

Apr 19, 2020

How to Build a Distributed Big Data Pipeline Using Kafka and Docker

How to Build a Distributed Big Data Pipeline Using Kafka and Docker

A Real-time Stream Processing App Example Exploring Twitter Sentiment and Weather Condition Correlation

Vignesh Perumal

Feb 12, 2021

Latest

Transforming Talent Management Experience with Job Market Data — GoodPeople

Transforming Talent Management Experience with Job Market Data — GoodPeople

Authors: Rovenna Chu, Ha Do, Andrew Han, Rakhi Lakhwani

Apr 15

Dish Out - A Restaurant Business Analysis Tool

Dish Out - A Restaurant Business Analysis Tool

Authors: Aneeqha Tahseen Syeda, Bhawna Arya, Mohamed Anan Anaikar, Neha Borulkar

Apr 14

TinyML: Micro Footprint, Macro Impact

TinyML: Micro Footprint, Macro Impact

Authors: Aditya Panchal, Divye Maheshwari, Hemang Bhanushali, Priyanka Manam, Rohit Irvisetty

Feb 11

Cracking The YouTube Algorithm

Cracking The YouTube Algorithm

Check out this article to know more about how the YouTube recommendation system works!

Swaathi Sundaramurugan

Feb 11

Terrific Data Scientist Found Unconscious After Deploying the Model Without MLOps

Terrific Data Scientist Found Unconscious After Deploying the Model Without MLOps

Feb 11

Catch Me If You Can — Getting the True Meaning out of Big Cloud of Texts

Catch Me If You Can — Getting the True Meaning out of Big Cloud of Texts

Authors: Rovenna Chu, Ha Do, Andrew Han, Rakhi Lakhwani

Feb 11

PCA: The right way

PCA: The right way

This blog is written and maintained by students in the Professional Master’s Program in the School of Computing Science at Simon Fraser…

Feb 11

Deep Dive into Animation Plot with Real-time Data

Deep Dive into Animation Plot with Real-time Data

Authors: Jiahe Wang, Zhi Zheng, Huiyi Zou, Shilin Wang, Hayden Yan

Feb 11

Are you ready for Machine-led Machine Learning? MAML: A Modern Approach to Meta-Learning

Are you ready for Machine-led Machine Learning? MAML: A Modern Approach to Meta-Learning

By: Gabriel Henderson, Shrey Grover, Kaumil Trivedi, Gurashish Singh & Arshdeep Singh

Feb 11

Picasso of the Future!

Picasso of the Future!

Authors: Akshita Sharma, Himani Naveen Joshi, Gokul Mohanarangan, Pranav Balaji, Shivek Chhabra

Feb 11

spaCy supremaCy is here, and here is why you shouldn’t sleep on it.

spaCy supremaCy is here, and here is why you shouldn’t sleep on it.

Feb 10

Adios Pandas! Process Big Data in a Flash using Terality, Dask, or PySpark

Adios Pandas! Process Big Data in a Flash using Terality, Dask, or PySpark

Check out this blog to operate large datasets with ease by changing just the import line!

Feb 10

Redis — the optimal solution for high-performance data retrieval

Redis — the optimal solution for high-performance data retrieval

Haoming Pan, Yukang Liu, Yewin Shu, Zheng Wu, Jie Min

Feb 10

In 20 minutes learn to conduct an A/B test

In 20 minutes learn to conduct an A/B test

Authors: Cheng Guo, Wenxiao Li, Jie Wang, and Yuke Wang.

Feb 10

Sailing through Kafka Streams

Sailing through Kafka Streams

Building distributed real time data streaming applications with Kafka Streams API.

Feb 10

What You Never Knew About Attention Mechanisms

What You Never Knew About Attention Mechanisms

Greg Mehdiyev, Ray Hong, Jinghan Yu, Brendan Artley

Feb 10

CNN: an eye for AI

CNN: an eye for AI

CNN Tutorial — Zero to Hero !

Feb 10

In-depth understanding of Apache Kafka in 10 minutes

In-depth understanding of Apache Kafka in 10 minutes

Authors: Danlei Qiang, Jingshan Feng, Sijia Cai, Tiange Wang, Yizhe Lyu

Feb 10

Learn K-Means and Hierarchical Clustering Algorithms in 15 minutes

Learn K-Means and Hierarchical Clustering Algorithms in 15 minutes

Authors: Haonan Wu, Jingyan Sun, Lingxiao Song, Ziyue Cheng

c733 data scientists

Feb 10

A Practical Guide to Support Vector Machines (SVM)

A Practical Guide to Support Vector Machines (SVM)

Authors: Wei Zhang, Wanyi Su, Zeyu Hu, Jinyao Lu, Yin Yu Kevani Chow

Feb 10

Docker: What You Need to Know as a Data Scientist

Docker: What You Need to Know as a Data Scientist

Authors: Bofei Jing, Shuo Qiu, Yifei Chen, and Heng Zhou

Feb 9

RAPIDS: The Future of GPU Data Science?

RAPIDS: The Future of GPU Data Science?

Authors: Aidan Vickars, Anant S Awasthy, Karthik Srinatha, Rishabh Kaushal

Rishabh Kaushal

Feb 9

A dashin’ plot: Beginner’s guide to Plotly & Dash

A dashin’ plot: Beginner’s guide to Plotly & Dash

Authors: Tanmay Jain, Ayush Raina, Siddhartha Haldar, Anirban Banerjee

Feb 7

Surviving In a Random Forest with Imbalanced Datasets

Surviving In a Random Forest with Imbalanced Datasets

CONTRIBUTORS: Bilal Hussain, Kyoun Huh, Hon Wing Eric Chan, Sakina Patanwala

Feb 13, 2021

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