Azure ML Part 9- Cross Validation: Machine Learning Prediction (6)

In the previous posts (from Part 1 to Part7), I have explained the whole process of doing machine learning inside the Azure ML, from import data, data cleaning, feature selection, training models, testing models, and evaluating. In the last post, I have explained one of the main ways of improving the algorithms performance name as “Tune Read more about Azure ML Part 9- Cross Validation: Machine Learning Prediction (6)[…]

Azure ML Part 8- Tune Parameters: Machine Learning Prediction (5)

In the previous posts from Part 1 to 7, I have explained how to do machine learning with Azure ML. I have explained some of the main components in Azure ML that helps us to do data wrangling, train the model, feature selection and evaluating the result. The data cleaning such as SQL transformation, select Read more about Azure ML Part 8- Tune Parameters: Machine Learning Prediction (5)[…]

Azure ML Part 7: A Machine Learning Prediction scenario (4)

In the previous posts from Part 1 to 6, I have explained how to do machine learning process. The data cleaning such as SQL transformation, select specific columns, remove missing values,  Edit meta data, and normalize data.  Also, I have explained how to find relevant attributes  using Feature Selection Feature to identify which feature are more Read more about Azure ML Part 7: A Machine Learning Prediction scenario (4)[…]

Azure ML Part 6: A Machine Learning Prediction scenario (3)

In previous posts (Part 4 and Part 5), I have explained some of the main components of Azure ML via a prediction scenario. In post one the process of data cleaning (using SQL Transformation, Cleaning Missing Value, Select specific Columns, and Edit Meta Data)  has been explained. and in the second Post, I have explained how to apply Read more about Azure ML Part 6: A Machine Learning Prediction scenario (3)[…]

Azure ML Part 5: A Machine Learning Prediction scenario (2)

In the previous Post , I start to do prediction the cancer diagnosis using some laboratory data. I have explained some of the main components for doing the data cleaning such as “SQL Transformation”, “Edit Meta Data”, “Select Columns” and “Missing Values”. In this post I am going to show the rest of data cleaning Read more about Azure ML Part 5: A Machine Learning Prediction scenario (2)[…]

Azure ML Part 4: A Machine Learning Prediction scenario (1)

In previous Posts Part 1, Part 2 and Part3  I have explain some about the azure Ml environment, how to import data into it and finally how to do data transformation using Azure ML component. In this post and the next one I am going to show how to do a Machine Learning in Azure Read more about Azure ML Part 4: A Machine Learning Prediction scenario (1)[…]

K-mean clustering In R, writing R codes inside Power BI: Part 6

In the previous post,I have explained the main concepts and process behind the K-mean clustering algorithm. Now I am going to use this algorithm for classifying my Fitbit data in power BI.   as I have explained in part 5, I gathered theses data from Fitbit application and I am going to cluster them using Read more about K-mean clustering In R, writing R codes inside Power BI: Part 6[…]

Clustering Concepts , writing R codes inside Power BI: Part 5

Sometimes we just need to see the natural trend and behaviour of data without doing any predictions. we just want to check how our business data can be naturally grouped. According to the Wikipedia , Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) Read more about Clustering Concepts , writing R codes inside Power BI: Part 5[…]

Over fitting and Under fitting in Machine Learning

The main aim of machine learning is to learn from past data that able us to predict the future and upcoming data. It is so important that chosen algorithm able to mimic the actual behaviour of data. in the all different machine learning algorithms, there is away to enhance the prediction by better learning from Read more about Over fitting and Under fitting in Machine Learning[…]

Have more Charts by writing R codes inside Power BI: Part 2

In the previous post (Part 1) I have explained how to write a simple scatter chart in the Power BI. Now in this post I am going to show how to present 5 different values in just one chart via writing R scripts. I will continue the codes that I wrote in the previous post  as below : Read more about Have more Charts by writing R codes inside Power BI: Part 2[…]