Tuesday, 18 April 2017

C# Corner Conference 2017 - Building Intelligent Bots

The C# Corner Annual Conference 2017 was a three-day annual event for software professionals and developers held in New Delhi, India. First day was exclusive for C# Corner MVPs only. The second day was open to the public, and includes presentations from many top names in the industry. The third day events are, again, exclusively for C# Corner MVPs.

The conference was awesome with about 600+ attendees in total. There were 3 tracks running in parallel each having a accommodating 200+ attendees.




Monday, 17 April 2017

Cloud, IoT, & Future of Tech Conference - Getting Started with Machine Learning

In April 2017 I was invited to speak at the C# Corner Conference in Delhi, India. As part of this trip, the organizers also invited me to speak at the Cloud, IoT, & Future of Tech Conference at the GLA University in Mathura, India.
Mathura is a city in the North Indian state of Uttar Pradesh and is about 5 hours drive from Delhi where I was staying. So, we had to wake up at 5 am and leave the hotel at 6 am to have a chance to speak at the conference at about 11. Yes - that's a long drive, but worth it! We could admire the nature and culture of the country while travelling from a city to a more rural area. We also had a great chat with our friend from the C# Corner team Ravi who explained us a lot about India and the culture. That was just some story about the trip:)


Well, we reached the university at about 11:30 and as we stepped in, we were all surprised by the big banner having all the speaker's names. Our surprise does not end here! As we entered the conference room, there was about 300+ students attending the conference! That's massive!

Sunday, 16 April 2017

Developers Conference 2017 - Improving Machine Learning Models

The third edition of the developers conference of Mauritius was held between the 30th of March and 1st of April 2017. The conference ran on 3 days with 3 tracks in parallel and had about 330+ attendees and 50+ speakers.

My third session at the DevCon was about the techniques that can be used to improve the performance of machine learning models.
The session was just after the introduction to Data Science that was presented by Arwin and myself.



I started with a summary of the data science process and presented the data set that shall be used in the demo.
Next, I explained the steps of data cleansing and made a live demo of same. The attendees were quite surprised that the model got an increase in accuracy of 10% just by doing the cleansing properly.
I then proceeded with more advanced techniques such as Feature Selection, Feature Scaling, Parameter Tuning and Cross Validation.

Saturday, 15 April 2017

Developers Conference 2017 - Introduction to Data Science

The third edition of the developers conference of Mauritius was held between the 30th of March and 1st of April 2017. The conference ran on 3 days with 3 tracks in parallel and had about 330+ attendees and 50+ speakers.

Data Science is definitely one of my favorite topics these days. I'ts amazing how data can be crafted and transformed to help us make better decisions by using predictive analytics. This year, I really wanted to deliver a level 300/400 session about Machine Learning. But, to do so, I needed to make a good introduction to the subject first. Therefore, with the help of Arwin, my friend from the MSP community, we worked together for 2 weeks to prepare a session about the introduction to Data Science.


Friday, 14 April 2017

Developers Conference 2017 - Microsoft MVP AMA

The third edition of the developers conference of Mauritius was held between the 30th of March and 1st of April 2017. The conference ran on 3 days with 3 tracks in parallel and had about 330+ attendees and 50+ speakers.
During the past year, I received several queries via social media about the Microsoft MVP Program like how to become one and the benefits of being a Microsoft MVP. This is why I decided to have a session about it to introduce the program and give the audience the opportunity to ask all the questions that they have. To help me, Joki (MVP) and Arnaud (DX) was also present to share their feedback about the MVP Program. 

Sunday, 19 February 2017

The Data Science Process with Azure Machine Learning

It’s no secret today that all our applications and devices are generating tons of data; thus making data analytics a very hot topic these days and Microsoft Azure has all the tools necessary to ingest, manage and process all these data, also called Big Data.
However, all these data in itself is not useful unless processed, interpreted and visualized correctly. Another power behind the data acquired through years is to make Predictive Analytics. That is, using the data to make forecast and predictions.
But, by only using the data gathered, it is difficult to make analysis. To use the data, it needs to be cleansed, transformed and processed to a format that we can use to build Predictive Models. This process is called the Data Science Process.
The Data Science Process
Before the “Buzz Words”, the Cross Industry Standard Process for Data Mining presented a a data mining process model that describes commonly used approaches that data mining experts use to tackle problems.

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As you can see in the illustration above, the model proposed consisted of not only technical steps but also focused on understanding the business process and applications before going to the data preparation, modelling and evaluation steps.

Wednesday, 28 December 2016

Xamarin + Azure: Part 4 - Intelligent Apps

Scope

The article shown below follows my presentation and demo at Xamarin Dev Days in Mauritius. The article demonstrates how to get started with Azure mobile apps and the benefits of the powers of Cloud in terms of scalability, Offline Sync, and Data Analytics.
This is the fourth part of the series, where we’ll use intelligent features of the app, using Microsoft Cognitive Services.


Introduction

The objective of this article is to build on the sample app discussed in part 3 and use Microsoft Cognitive Services to calculate the sentiment score of the feedback to determine whether it is positive or a negative feedback.

Microsoft Cognitive Services lets you build apps with powerful algorithms, using just a few lines of code. They work across the devices and platforms such as iOS, Android and Windows, keep improving, and are easy to set up.

To reach this goal, the Text Analytics API of Microsoft Cognitive Services shall be used.


Text Analytics API

Text Analytics API is a suite of text analytics Services built with Azure Machine Learning. It currently offers APIs for sentiment analysis, key phrase extraction, and topic detection for English text, as well as language detection for 120 languages.



Sunday, 18 December 2016

TechNet Guru Awards November 2016!

The TechNet Guru Awards celebrate the technical articles on TechNet, contributed from valued wiki authors like YOU!
Each month, the contributions are scored by a panel of judges (5 per category, 2-3 in each are MS experts), and the winners of each category are showered with love and attention from all corners of TechNet.

This month, my article about Xamarin + Azure won the bronze award.


Monday, 28 November 2016

Xamarin + Azure: Part 3 – Offline Sync

Scope
The following article covers a presentation and demo at Xamarin Dev Days in Mauritius. The article demonstrates how to get started with Azure Mobile Apps and benefit the powers of the cloud in terms of Scalability, Offline Sync and Data Analytics.
This is the third part of the series where offline sync capabilities shall be added to the application.

Introduction

The objective of this article is to build on the sample app discussed in part 2 and add offline sync capabilities to it.
 People using mobile apps are often on the move and are not always connected. Despite not having connectivity, the application users’ needs to be able to continue working and retrieve their data in offline mode.
To achieve this, the Azure Mobile Service SDK provides offline sync capabilities using SQL Lite as local storage.

Implementation

To add offline sync, both the front end and the back end code of the client needs to be modified. Follow the steps below to proceed with the change.

Install SQL Lite

Install the NuGet package Microsoft.Azure.Mobile.Client.SQLiteStore in both the portable class and all the clients that will consume the service.

Saturday, 26 November 2016

Xamarin + Azure: Part 2 – Extend the Sample App


Scope
The following article covers a presentation and demo at Xamarin Dev Days in Mauritius. The article demonstrates how to get started with Azure Mobile Apps and benefit the powers of the cloud in terms of scalability, Offline Sync and Data Analytics.
This is the second part of the series where we’ll extend the sample app discussed in part one.

Introduction

The objective of this article is to build on the sample app discussed in part 1 and add custom logic.
In this demo, an App that will allow the attendees of Xamarin Dev Days to give feedback to the organizers will be created. The application will store the attendee name, the attendee feedback and a sentiment score.

Modifying the Cloud Back End

Adding the Data Object

The first step is to add the data object. Therefore, create a new call called Feedback.cs in the DataObjects folder
Make sure that the class inherits from EntityData from Microsoft.Azure.Mobile.Server and add the attributes of the model as below.