Tung Thanh Le's repositories
Deep-Learning
Implemented the deep learning techniques using Google Tensorflow that cover deep neural networks with a fully connected network using SGD and ReLUs; Regularization with a multi-layer neural network using ReLUs, L2-regularization, and dropout, to prevent overfitting; Convolutional Neural Networks (CNNs) with learning rate decay and dropout; and Recurrent Neural Networks (RNNs) for text and sequences with Long Short-Term Memory (LSTM) networks.
Machine-Learning
Machine learning techniques, such as Linear Regression, Logistic Regression, Neural Networks (feedforward propagation, backpropagation algorithms), Diagnosing Bias/Variance, Evaluating a Hypothesis, Learning Curves, Error Analysis, Support Vector Machines, K-Means Clustering, PCA, Anomaly Detection System, and Recommender System.
SDC-term1-Advanced-Lane-Finding
Detected highway lane boundaries on a video stream with OpenCV image analysis techniques, including camera calibration matrix, distortion correction, color transforms, gradients, etc., to create a thresholded binary image, a perspective transform to rectify binary image ("birds-eye view"). Detected lane pixels and fit to find the lane boundary, determined the curvature of the lane and vehicle position with respect to center. Warped the detected lane boundaries back onto the original image.
basic_reinforcement_learning
An introductory series to Reinforcement Learning (RL) with comprehensive step-by-step tutorials.
data-engineering-gcp
Data Engineering on Google Cloud Platform
SDC-term1-Traffic-Sign-Classifier
Built and trained a deep neural network to classify traffic signs, using TensorFlow. Experimented with different network architectures. Performed image pre-processing and validation to guard against overfitting. The datasets are collected from the German Traffic Sign for training and random traffic signs downloaded from internet for testing.
SDC-term2-Model-Predictive-Control
Implemented Model Predictive Control to drive the vehicle around the track (even with additional latency between commands).
120-DS-Interview-Questions
My Answer to 120 Data Science Interview Questions
aws-lex-web-ui
Sample Amazon Lex chat bot web interface
beam-example
Apache Beam example
Coding-Interview-Challenge
Python concise solutions to the Leetcode problems.
competitive-data-science-1
How to Win a Data Science Competition: Learn from Top Kagglers
DataflowJavaSDK
Google Cloud Dataflow provides a simple, powerful model for building both batch and streaming parallel data processing pipelines.
donation-analytics
As a data engineer working for political consultants whose clients are cash-strapped political candidates. They've asked for help analyzing loyalty trends in campaign contributions, namely identifying areas of repeat donors and calculating how much they're spending. Identify areas (zip codes) that could be sources of repeat campaign contributions.
kaggle-past-solutions
A searchable compilation of Kaggle past solutions
models
Models and examples built with TensorFlow
object-detection
Detect a Phone or not a Phone in the images. Use Logistic Regression to classify the images. Prediction accuracy is achieved at 96.15%.
python-reference
Python Reference (The Right Way)
reinforcejs
Reinforcement Learning Agents in Javascript (Dynamic Programming, Temporal Difference, Deep Q-Learning, Stochastic/Deterministic Policy Gradients)
self-driving-demo
Distributed TensorFlow implementation of steering angle prediction model for self-driving car. Includes integration to run on ClusterOne.
spatial-transformer-network
A Tensorflow Implementation of Spatial Transformer Networks