DataTechNotes: Looking Back on the Year 2018

There are only a few days left in 2018. And I think it is time to look back and reflect on what we have done during the year. DataTechNotes has offered 50 articles in a field of data science in this year. Readers visit this blog from different parts of the world every day. As an author of DataTechNotes, I tried to publish a new article every week and I can say that I've accomplished this goal. This is what I can proud of it so far. Consistency is a key factor in doing projects. Small daily steps towards the goal lead to big achievements.

While writing the tutorials I gained some lessons that I would like to share with you.

Consistency is a critical factor in whatever you do.
Focus and goal give motivation.
The teacher gets the best lessons for himself by teaching others.
Writing is an arrangement of scattered ideas in your mind, and it improves learning ability.
Helping people gives you joy and fulfillment.

To write a new article, it took a few hours, sometimes weeks to organize the ideas in my mind. We've been studied various topics of data science from basic concepts to advanced ones. The topics include the classification, regression, anomaly detection, boosting, deep learning and neural network models, regularization, recurrent neural networks, and others during the year. Example source codes are presented in R, Python, and C# programming languages.

Here, you may check and read all the posts during the year.

December 2018

RNN Example with Keras SimpleRNN in Python
Time series data prediction with LSTM model in python
Cross-validation in R
Classification with Gaussian Naive Bayes model in Python
Forecasting time series data in Python

November 2018

Classification with Random Forests in Python
Classification with CART model in R
Understanding Max-Pooling of Image Data with R
Dynamic Time Warping Example in R

October 2018

Classification with Learning Vector Quantization in R
LDA Classification in R
Understanding Elastic Net Regularization with R
Understanding Ridge regularization with R
Understanding Lasso regularization with R

September 2018

How to Run R Script from C# Program in a Session
Regression Example with ML.NET in C#
Classification Example with ML.NET in C#
Image Convolution Example in R
Classification with Logistic Regression in Python

August 2018

Understanding Bias and Variance in Model Fitting
Deep Learning with Keras in Python
Deep Learning with Keras in R
K-means clustering with sklearn in Python

July 2018

Classification with MXNet in R
Gradient Descent with Linear Regression model in R
Classification with 'maboost' in R
LogitBoost classification sample in R