07 Feb, 2016
FYI, the course link is https://www.udacity.com/course/deep-learning--ud730. This course takes approximately 3 months with assumption 6hrs/wk (work at your own pace).
14 Nov, 2015
On 10th November, I saw the news that Google open sourced Tensorflow. As a programmer that is passionate towards AI, this is a thing that I must try out.
31 Oct, 2015
Recently Julia is on the trend, due to its purpose of becoming an easy-to-use scripting language, while giving near to C performance speed. I always see it as combination of Python + R + C, while some might think it as Python + Matlab + C
04 Jul, 2015
This course provides a broad introduction to machine learning, datamining, and statistical pattern recognition. Topics include:
- Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks).
- Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning).
- Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI).
20 Jun, 2015
Kaggle titanic challenge is a famous knowledge competition which many new Kaggler will try their first Kaggle competition. Since there are currently no tutorial to solve this challenge with artificial neural network, I decided to use torch7 to compete in this competition. FYI, click here to get the data.
05 Jun, 2015
Bike sharing systems are a means of renting bicycles where the process of obtaining membership, rental, and bike return is automated via a network of kiosk locations throughout a city. Using these systems, people are able rent a bike from a one location and return it to a different place on an as-needed basis. Currently, there are over 500 bike-sharing programs around the world.
24 May, 2015
Backpropagation, is a well known learning algorithm in neural network. In the algorithm, the weight calculated is based on the out put of the result. To prevent overfitting and introduce more uncertainty, its often comes with L1 and L2 regularization.
Weights with greater uncertainty introduce more variability into the decisions made by the network, leading naturally to exploration