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How to set JSON as a data source to a Combo Box in Power Apps

I was creating a form mockup in Power Apps. Since it was a mockup, I didn't want to connect to any data source. One of the fields in the form was Combo Box. When you add this control, by default the Items property is set to ComboBoxSample . When you run the app, the combo box shows values such as Item 1, Item 2,... Item 15. For the purpose of the mockup, I wanted to put some other values to this control. However, creating a table and connecting to that data source is over engineering for a mockup. Hence, I wanted to create a sample JSON object and assign that to Items property. This is where things got little tricky. I tried forming JSON text something like below (the same example given in Microsoft website). [ { "id": 1, "name": "Option 1"}, { "id": 2, "name": "Option 2"}, { "id": 3, "name": "Option 3"} ] When I put this in Items property, it showed errors like below for the string part ...
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Microsoft Reactor Event on AI

Recently I attended Microsoft Reactor event on Architecture Recipes for AI-Powered Applications . The speaker was Harun Raseed Basheer. The speaker started with a brief introduction to AI and ML. Later he covered topics such as Vector Search, Cosine Similarity, RAG Model, Agentic AI, Prompt Engineering, and Tokens. The first 1 hour was theory and demonstration. The next 40 mins or so was creating an AI project hands-on on Azure. In Azure, I created AI Hub and then AI Project. This project used GPT to create a chat application. With this exercise I also explored various models available to use and how to check the pricing for each model. I also checked how this application code can be viewed and then customized to our specific requirements. This session was good. The speaker was knowledgeable and patiently answered the questions. I also got exposure to building an Agentic AI applications in Azure. This definitely gives me a window to explore other possibilities and opportunities in AI A...
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It's changed!

It's changed now! The domain as well as the scope of this site. All my technical learning will be shared in this blog. It's not specific to any one or two technoligies. Rather, any technology which I come across and learn which I feel like sharing with others, I'll publish in this site. I hope to keep my writing as regular and consistent as possible. Let's see, how it goes!
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Changes in this site

For almost 2 years, I did not write anything here! Not that I had nothing to learn or write, but I was heavily occupied with some professional engagements. I'm back now and with some changes. When I created this site, I was planning to keep this site dedicated to the world of Data Science and ML. But a lot of things have changed in my professional career. Hence, I'll be changing a few things in this site as well. Let me first share what has changed in my professional life. I was a SharePoint professional for more than a decade. I started my journey with SharePoint somewhere in 2007 as a Developer and grew as a Team Lead, Architect and then Senior Architect. Anything around SharePoint was my comfort zone! If people come to me with a requirement, I can confidently say whether SharePoint is the right tool for this or not. And if it is the right tool, what would be the architecture and design of the application would be. As they say, being in a comfort zone for long may not be good...
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Ordinal Encoder, OneHotEncoder and LabelBinarizer in Python

Usually in the data set we work on, we will have both numerical data as well as categorical data (non-numeric). There are algorithms which do not work on categorical data. These algorithms are designed that way to enhance efficiency. So in such cases how do we train the model with categorical data? This is where we need to apply a technique called Encoding. Encoding transforms categorical data into numeric. There are various Encoders available in sci-kit learn library. In this post, I'll share my learning on three Encoders. Ordinal Encoder This performs ordinal (integer) encoding of categorical data. Let's look at an example. I have an array of categorical data. This is a 2 dimensional array. multiArray = np.array([[ 'Karnataka' ,  'KA' ], [ 'Maharastra' ,  'MH' ], [ 'Gujarat' ,  'GJ' ]]) Then I use OrdinalEncoder to transform this data. ordinalEncoder = OrdinalEncoder() ordinalEncoderArray = ordinalEncoder.fit_transform(mult...
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My first Kaggle competition - Women in Data Science (WiDS) 2021

As a beginner to the Data Science and ML world, I had no idea how these competitions will be. I always thought such competitions were for the experts. And then I happened to attend a session from Kaggle Expert Usha who decoded many aspects of a competition in Kaggle and motivated me and others to take part in the competition. The competition was " Women in Data Science (WiDS) Datathon 2021 ". This competition's purpose was to inspire women to learn about data science and also to create a supportive environment. This competition was open to males as well, however at least 50% of the members in the team should be women. So I partnered with my friend and ex-colleague. This year's competition focused on models to determine whether a patient admitted to an ICU has been diagnosed with a particular type of diabetes, Diabetes Mellitus. Usha had shared a notebook with a lot of background work done for this problem. So her notebook became a bible to understand the whole proces...
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Joined Kaggle

From the last 2-3 months, I was playing around Kaggle . Kaggle is the world's largest data science community. What is exciting about this site is it provides a platform to participate in data science competitions to learn and evaluate our learning and knowledge.  Another exciting feature in Kaggle is we can create "Notebooks" which is basically a workbench to try and execute the code! As I'm using Python in my learning journey, I was able to write Python code using all the supported libraries to execute my code. There are a lot of courses as well to learn the new skillset, though I've not tried this yet. There is a discussion forum where we can ask questions and get answers from the community. There are a plenty of data sets available which we can use for learning purpose. Gamification is part of this platform, so users get "rankings" based on their activities and how their contributions were received by the community users. That means - all you need to ...
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