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followers: 2.0 following: 1.0 repos: 34.0 gists: 0.0

Name: Johannes Chin

Type: User

Company: TikTok

Bio: Analytical and detail-oriented Data Scientist with proven records of success in the collection and manipulation of large datasets.

Location: Ireland

Blog: https://ie.linkedin.com/in/johanneschin

Johannes Chin's Projects

android_nanodegree_app_portfolio

This project displays apps that will be built as part of the Android Nanodegree.

connect_four_java_game

This is the final project for Intro to Java Programming course. I am tasked to to create a game-playing agent to play Connect Four.

coursera_machine_learning

Coursera machine learning course tought by Andrew Ng

credit_card_fraud_detection

Anonymized credit card transactions labeled as fraudulent or genuine

data-engineering-nanodegree

Solution to all projects of Udacity's Data Engineering Nanodegree: Data Modeling with Postgres & Cassandra, Data Warehouse with Redshift, Data Lake with Spark and Data Pipeline with Airflow.

end_to_end_cnn_tensorflow

End to end process on how to classify images via Tensorflow.

feed_forward_neural_network_via_tensorflow

Step by step tutorial on how to deploy feed forward neural network via Tensorflow.

gender_voice_recognition_neural_network_mlp_via_tensorflow

Classify gender voice via Neural Network.

gradient_descent_algorithm_via_numpy

Construct a simple gradient descent algorithm via Numpy

grokking_algorithms

Code for the book Grokking Algorithms (https://amzn.to/29rVyHf)

hse_advanced_machine_learning_nlp

Natural Language Processing

iris_classification_via_keras_and_scikit-learn

Perform machine learning classification via Keras and hyper-parameter tuning via GridSearchCV

kaggle_dogs_vs_cats_redux_kernels_edition

Distinguish images of dogs from cats.

kaggle_house_prices_advanced_regression_techniques

Ask a home buyer to describe their dream house, and they probably won't begin with the height of the basement ceiling or the proximity to an east-west railroad. But this playground competition's dataset proves that much more influences price negotiations than the number of bedrooms or a white-picket fence. With 79 explanatory variables describing (almost) every aspect of residential homes in Ames, Iowa, this competition challenges you to predict the final price of each home. The potential for creative feature engineering provides a rich opportunity for fun and learning. This dataset lends itself to advanced regression techniques like random forests and gradient boosting with the popular XGBoost library. We encourage Kagglers to create benchmark code and tutorials on Kernels for community learning. Top kernels will be awarded swag prizes at the competition close. Achieved top 51% via the following code.

kaggle_instacart_market_basket_analysis

In this competition, Instacart is challenging the Kaggle community to use this anonymized data on customer orders over time to predict which previously purchased products will be in a user’s next order.

kaggle_quora_question_pairs

Can you identify question pairs that have the same intent?

kaggle_the_nature_conservancy_fisheries_monitoring

Can you detect and classify species of fish?

kaggle_two_sigma_connect_rental_listing_inquiries

Finding the perfect place to call your new home should be more than browsing through endless listings. RentHop makes apartment search smarter by using data to sort rental listings by quality. But while looking for the perfect apartment is difficult enough, structuring and making sense of all available real estate data programmatically is even harder. Two Sigma and RentHop, a portfolio company of Two Sigma Ventures, invite Kagglers to unleash their creative engines to uncover business value in this unique recruiting competition.

machine_learning_engineer_nanodegree

Machine learning represents a key evolution in the fields of computer science, data analysis, software engineering, and artificial intelligence. This program will teach you how to become a machine learning engineer, and apply predictive models to massive data sets in fields like finance, healthcare, education, and more.

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