Ever wondered how Google assistant and Siri can speak with us exactly like humans. This is the magic of Deep Learning.

So without wasting time let’s jump directly to the topic.

Essential guide to various dimensionality reduction techniques in Python

Exploratory Data Analysis is an important component of the data science model development pipeline. A data scientist spends most of the time in data cleaning, feature engineering, and performing other data wrangling techniques. Dimensionality Reduction is one of the techniques used by data scientists while performing feature engineering.

Dimensionality Reduction is the process of transforming a higher-dimensional dataset to a comparable lower-dimensional space. A real-world dataset often has a lot of redundant features. Dimensionality reduction techniques can be used to get rid of such redundant features or convert the n-dimensional datasets to 2 or 3 dimensions for visualization.

In this…

Google is a massive company that employs tons of data scientists, so let’s see what Google uses for their data science teams. Now, the process of me finding this information was fairly basic, I went to their career page, searched for Data Science positions, and noted the most frequent languages, packages and tools I saw them use:

From collecting data to sending results, ADF constructs the right MLOps Lifecycle on one screen

The impression I had for implementing Machine Learning up to 3 years back was that of building a model in Python and deploying the project to an automated CI/CD pipeline. While it solved the basic criteria of performing predictions, it could never be called an end-to-end workflow because data storage and reporting were two significant components missing in this workflow and had to be dealt with separately. In this article, I will walk through an entire Machine Learning Operation Cycle and show how to establish every step of the way using Azure Data Factory (ADF). Yes, it is possible, easy…

A collection of best online courses to learn Microsoft Azure Cloud Platform and Azure DevOps in depth

Hello guys, if you want to learn about the Microsoft Azure Cloud Platform in-depth and looking for the best online training courses then you have come to the right place. In the past, I have shared the best courses to prepare for Azure Fundamentals, Azure Administrator, and Azure Architect certifications, and today I am going to share the best online course to learn Azure platform for Beginners.

These are top-quality courses from expert trainers and instructors and picked from websites like Udemy, Coursera, Pluralsight, and edX.

You can use these courses to not only learn Microsoft Azure core services but…

A year and a half ago, I dropped out of one of the best computer science programs in Canada. I started creating my own data science master’s program using online resources. I realized that I could learn everything I needed through edX, Coursera, and Udacity instead. And I could learn it faster, more efficiently, and for a fraction of the cost.

I’m almost finished now. I’ve taken many data science-related courses and audited portions of many more. I know the options out there, and what skills are needed for learners preparing for a data analyst or data scientist role.

In neural networks, Convolutional neural network (ConvNets or CNNs) is one of the main categories to do images recognition, images classifications. Objects detections, recognition faces etc., are some of the areas where CNNs are widely used.

CNN image classifications takes an input image, process it and classify it under certain categories (Eg., Dog, Cat, Tiger, Lion). Computers sees an input image as array of pixels and it depends on the image resolution. Based on the image resolution, it will see h x w x d( h = Height, w = Width, d = Dimension ). Eg., …

The fastest way to learn how Blockchains work is to build one

You’re here because, like me, you’re psyched about the rise of Cryptocurrencies. And you want to know how Blockchains work — the fundamental technology behind them.

But understanding Blockchains isn’t easy — or at least wasn’t for me. I trudged through dense videos, followed porous tutorials, and dealt with the amplified frustration of too few examples.

I like learning by doing. It forces me to deal with the subject matter at a code level, which gets it sticking. …

In this post, I’ll show how I used Python code within Tableau to build an interactive dashboard implementing a time-series forecast. If you just want to play around with the dashboard first and explore the SARIMAX algorithm, download the full python-implemented dashboard here or go to this slightly dumbed-down version on Tableau Public (Tableau Public wisely but disappointingly disallows external scripts to be uploaded, so I had to fake the Python scripts with hard-coded data sets).

TabPy: Because when you can’t think of a good name, try a portmanteau

Last year, Tableau released version 10.2 which included integration with Python. It’s not super straightforward how to use it though, so I thought I’d…

Deep learning is a subset of machine learning, a branch of artificial intelligence that configures computers to perform tasks through experience. Here’s a deep dive.

Deep learning, an advanced artificial intelligence technique, has become increasingly popular in the past few years, thanks to abundant data and increased computing power. It’s the main technology behind many of the applications we use every day, including online language translation and automated face-tagging in social media.

This technology has also proved useful in healthcare: Earlier this year, computer scientists at the Massachusetts Institute of Technology (MIT) used deep learning to create a new computer…

Harsh Dalal

Consultant & Trainer | Artificial Intelligence | Machine Learning | Deep Learning | Blockchain | Tableau

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