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

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 CART model in R

Understanding Max-Pooling of Image Data with R

Dynamic Time Warping Example in R

October 2018

LDA Classification in R

Understanding Elastic Net Regularization with R

Understanding Ridge regularization with R

Understanding Lasso regularization with R

September 2018

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

Deep Learning with Keras in Python

Deep Learning with Keras in R

K-means clustering with sklearn in Python

July 2018

Gradient Descent with Linear Regression model in R

Classification with 'maboost' in R

LogitBoost classification sample in R

June 2018

Hololens object rotation with gesture

Linear Regression Model Example in Python

May 2018

How To Install Shiny Server on CentOS 7

Solving R crash while loading keras dataset in centos 7

Classification with 'bagging' function in R

April 2018

Forecasting time series data in R

Running R script from C# program

March 2018

Classification with XGBoost Model in R

Classification with Adaboost Model in R

Classification with Gradient Boosting Model in R

February 2018

Polynomial regression curve fitting in R

T-test in R

Bayesian Network in R

Z-score calculation with R

January 2018

Outlier check with kmeans distance calculation in R

Outlier check with SVM novelty detection in R

Understanding data variable types in statistics

Thank you very much for visiting this blog and reading my articles. I hope, you will find them helpful.

*Best wishes!*

Thank you, Yorkinov, for sharing the knowledge. Why not share your life experience also, as other menu of technology. Wondering what is 'behind the scenes'. :)

ReplyDeleteYou're welcome! Thank you for your suggestion!

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