You may have used or seen filters in Instagram reels of cartooned people or colouring backgrounds or smoothing the face while taking the picture on your camera. The general meaning
What happens when the organisations experience an exodus of employees and remain clueless “why”? Or, when they’re unable to improve the sales for a key category in a very important
The Singapore Government has published a Model for AI Governance Principles that aims to increase trust in AI.
For text data, the term-document matrix is a kind of representation that helps in converting text data into mathematical matrices
The audio data is also sequential data where it can be considered as a signal which has modulation with time similarly to the time series data where data points are
ktrain is a lightweight wrapper library for TensorFlow Keras. It can be very helpful in building projects consisting of neural networks. Using this wrapper, we can build, train and deploy
in the self supervised learning process we are mainly focused about making the data workable to the downstream algorithms. but when using the self-supervised learning we make the data specifically
When it comes to determining whether a business will succeed or fail, time is the most important factor.
Image restoration techniques such as image super-resolution (SR), image denoising, and JPEG compression artefact reduction strive to recreate a high-quality clean image from a low-quality degraded image.
In many of the cases, we see that the traditional neural networks are not capable of holding and working on long and large information. attention layer can help a neural
IceVision is a framework for object detection which allows us to perform object detection in a variety of ways using various pre-trained models provided by this framework. It also offers
The main focus of the article is to implement a VARMA model using the Grid search approach. Where the work of grid search is to find the best-fit parameters for
Segmenting and tracking the objects of interest in the video is critical for effectively analyzing and using video big data.
two-phase machine learning algorithm if uses two algorithms together where the first algorithm is used for imputing variables of the dataset and the second algorithm is used to predict the
Plotly Express is a free and open-source Python visualization library for creating interactive and beautiful visualizations.
Precision and Recall are two of the most important metrics to look at when evaluating an imbalanced classification model. These help us to find out what fraction of the actual
It is important to understand the limitations that prevent machine learning adoption in many industries.
In this article, we are going to see how we can remove noise from the image data using an encoder-decoder model.
arbitrary information of the data and represent the result in an expressive context of their mean can be considered as the deep relational learning process and we can call
Implementing neural networks necessitates the use of a variety of specialized building elements, such as multidimensional arrays, activation functions, and automatic differentiation.
Meta Reinforcement learning(Meta-RL) can be explained as performing meta-learning in the field of reinforcement learning. where including meta-learning models in reinforcement learning we can grow the model to perform a
In this post, we will walk through the fundamental principles of the Bayesian Network and the mathematics that goes with it. Also, we will also learn how to infer with
Parallel computing is a sort of computation that performs several calculations or processes at the same time.
Multilevel modelling is a technique for dealing with data that has been clustered or grouped. Data with repeated measures can also be analyzed using multilevel modelling.
A Hoeffding tree is an incremental decision tree that is capable of learning from the data streams. The basic assumption about the data is that data is not changing over
As we have been using graphs to represent semantic relationships between different entities through nodes and arcs, similarly, the knowledge graph is used to model the relationships between entities as
Many machine learning packages require string characteristics to be translated to numerical representations in order to the proper functioning of models.
Learning the similarity between objects has a dominant role in human cognitive processes and artificial systems for recognition and classification.
The information gained in the decision tree can be defined as the amount of information improved in the nodes before splitting them for making further decisions.
Measuring the performance of any machine learning model is very important, not only from the technical point of view but also from the business perspective.
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