Photo by Kyle Glenn on Unsplash

In this post, we’ll go over how to put the survival plots and models we discussed in Part I into practice, the most interesting part of learning is its practical implementation. First, let look at our dataset and understand.

This dataset is of prostate cancer:

Before I get started with the survival review, I’d like to point out that this article is split into two parts. Part I will cover the fundamentals of survival analysis, followed by Part II, which will include some fantastic examples. Suggest reading both sections to get a full understanding. Let’s talk about survival analysis and its fundamental terms now.

Survival Analysis is a sub-discipline of statistics. It actually has several names. In some fields, it is called event-time analysis, reliability analysis, or duration analysis. …

What Is Sentiment Analysis?

Conclusions are integral to practically all human exercises and are key influencers of our practices. Our convictions and impression of the real world, and the decisions we make, are, to an impressive degree, molded upon how others see and assess the world. Therefore, when we have to settle on a choice, we regularly search out the assessments of others. Opinions and its related concepts such as sentiments, evaluations, attitudes, and emotions are the subjects of the study of sentiment analysis.

The commencement and quick development of the field match with those of the web-based media on the Web, e.g., surveys…

Why Is Model Interpretability so Important?

Simulated intelligence is mind-blowing in desire precision, measure viability, and assessment proficiency. In any case, computers normally don’t explain their desires. This transforms into a limit to the gathering of AI models. If the customers don’t trust in a model or a desire, they won’t use or send it. Hence the issue is the methods by which to help customers with trusting in a model.

While simpler classes of models (such as linear models and decision trees) are often readily understood by humans, the same is not true for complex models (e.g., ensemble methods…

Activation Functions:

A significant piece of a neural system Activation function is numerical conditions that decide the yield of a neural system. The capacity is joined to every neuron in the system and decides if it ought to be initiated (“fired”) or not, founded on whether every neuron’s info is applicable for the model’s expectation. Initiation works likewise help standardize the yield of every neuron to a range somewhere in the range of 1 and 0 or between — 1 and 1.

Progressively, neural systems use linear and non-linear activation functions, which can enable the system to learn complex information, figure and…

What is Word Embeddings?

In extremely simplified terms, Word Embeddings are the writings changed over into numbers, as there might be diverse numerical portrayals of a similar book. Be that as it may, before we jump into the subtleties of Word Embeddings, the accompanying inquiry ought to be posed — Why do we need Word Embeddings?

For reasons unknown, many Machine Learning calculations and practically all Deep Learning architectures are not capable of handling strings or raw content in their crude structure. They require numbers as contributions to play out such a vocation, be it grouping, relapse, and so forth in broader terms. …

The Sign Language is a strategy for correspondence for hard of hearing — moronic individuals. The gesture-based communication is a significant technique for correspondence for hard of hearing specially-abled people. As communication via gestures is all around organized code signals, each motion has a significance allotted to it.

It can be utilized to communicate complex implications by joining fundamental components. Over the most recent quite a long while there has been an expanded enthusiasm among the specialists in the field of gesture-based communication acknowledgment to present methods for connection from human-human to human — PC cooperation.

Many research works related…

PyTorch is a famous open-source machine learning library for Python developed by Facebook’s AI research group. PyTorch believes in a dynamic graph, unlike TensorFlow that creates a static graph. PyTorch supports both CPU and GPU computations.

In this post, we will see the “HELLO WORLD” of the Machine Learning model with a very famous dataset available for image classification i.e. Fashion_MNIST dataset, in which we will for a given image if it’s a clothing item(differentiating between all sorts of top-wear bottom wear for both the sexes), footwear or a bag. Thus, determining its probabilities to which class it belongs.


The moment you hear of face recognition, you think of surveillance in videos, that you are being watched. Over the last few decades, face recognition has become a popular area of computer vision. Face recognition systems use computer algorithms to pick out specific, distinctive details about a person’s face.

In this post, you will learn how to perform a basic implementation of facial recognition using OpenCV and Python. OpenCV essentially stands for Open Source Computer Vision Library. By the end, you will learn to detect faces in image and video.

Implementation of face Detection using OpenCV:

1. Install OpenCV, if…

Photo by Tobias Fischer on Unsplash

It’s pretty clear that in the past decade Python and R are being used commonly everywhere both as a tool and as open-source programming. R is considered as the best for statistical implementation while Python, on the other hand, is preferred for data analysis and building production-ready models. The easiest way to store data in native formats but in real-world implementations data is seldom read from CSV files. It’s is either sourced from data lakes or captured in the database from data streams.

The cloud comes into picture when handling and storing large chunks of data is required. With the…

Afaf Athar

I Do Data. I write what I wish I could have read when I was younger

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