This article is a review of a pre-release copy of the book “Wrong Fit, Right Fit” written by Dr. Andre C Martin. The book rightly communicates a right fit is similar to that of writing with our dominant hand, it is easy, almost automatic, and results in a readable sentence. On the contrary, the wrong …
An activation function in deep learning is a nonlinear transformation applied to the node output before passing it to the consequent layers in neural networks. Artificial Neural Networks (ANN) consist of multiple layers interconnected. Mainly there will be an input layer, output layer and one or more hidden layers. Inspired by the biological neural networks, …
Large language models (LLM) are general purpose language models in deep learning. The foremost word “Large” in LLM indicates a large training dataset which is often in the petabyte scale with an enormous number of parameters. General purpose means the models are capable of handling common problems in our day today life. The BERT model …
Sputtering is a physical vapour deposition (PVD) method use for thin film growth. Like any other physical vapour deposition, sputtering involves the deposition of an atom, ion or molecule corresponding to a target material onto the substrate. Sputtering employs electrical generation of plasma between the target material, which is the material to be deposited and …
We have published seven modules of interview questions in machine learning and answers so far on this website. This is yet another addition to the series of discussion on frequently asked questions in machine learning job roles. Whether stochastic gradient descent or gradient descent is computationally complex? Gradient descent is computationally complex. After identifying a …
Defining neural network architecture is a key step in deep learning. A lot of decisions have to be made regarding the architecture, number of nodes, activations function, regularization etc. One of the the important aspect is combining multiple inputs parallely and passing it to the next layer. This is done using the Functional API of …
A lot of useful applications of machine learning use deep learning as the backbone technology. Deep learning is the key reason behind the second wave of AI we see these days. A deep learning engineer solving various problems might be using various deep learning libraries on a day to day basis. Tensorflow and Keras are …
Hello World, In this article let us take a look at the process of matrix multiplication from a different perspective. Often matrix multiplication is taught or learned as a boring process of certain rules. This spoils the fun of doing it. So why don’t we look for better way to think about it by having …
Transcription factors are proteins that play a crucial role in gene expression, which is the process by which genes are turned on or off in cells. These proteins bind to specific DNA sequences in the promoter region of a gene and regulate the transcription of that gene into RNA, which is then used to make …
Ensemble models in machine learning combine the output of multiple models to build a better performing model as compared to the individual models. The individual models whose output are used for the process of ensemble modeling are called baseline models or base estimators. The objective behind this approach of ensemble learning is to alleviate the …