Businesses these days are generating and consuming a huge amount of data. This data varies in variety, volume, velocity, and veracity (4Vs of big data). Consequently, this trend has led to organizations’ rapid adoption of different AI and ML tools and techniques. Hence, converting a business problem to a machine...
In this article, we will go through some of the most commonly used open-source AI tools available in the market. This is not an exhaustive list. But it serves as a good starting point for anyone trying to venture into machine learning or artificial intelligence. Since these are open-source AI...
Natural Language Processing has gained a lot of popularity owing to an exponential increase in unstructured data generation. Here are some fun data to give you context – The world sees 682 million tweets per day There exists 1.2 million new data producing social media users each day Up to...
In this article, we will explore recurrent neural networks. For all the readers who are not versed with the concept of neural networks, I will recommend that you go through one of our previous articles and get a basic understanding of how a neural network works. Disclaimer – The concepts...
Data distributions lie at the heart of all the machine learning algorithms and data science techniques. A machine learning algorithm is only as good as the data it gets. Hence, it is important to fully understand the data and data distributions before we build our models. Consequently, explore and understand...
There has been a rapid advancement in technology and machine learning in the past decade. This has been accompanied by accelerated and innovative growth in the field of cloud computing. For example, Google introduced TPUs which are now available through Google Colab. And one can use it to experiment and...
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