The Fundamentals of Deep Learning for Computer Vision

The Fundamentals of Deep Learning for Computer Vision

This workshop will teach you the basics of deep learning for computer visualisation. This workshop will teach you how to train and deploy neural networks. You will also learn how to train your model to accurately recognize the type of an image. Deep learning is used to improve the performance and accuracy of your computer … Read more

What is Outliner in Data Science and How Does It Work?

What is Outliner and How Does It Work

Outliers are data points that are outside the expected range. The problem with outliers is that they spoil a dataset, so data scientists must be prepared to deal with them. The most common decision is whether to include an outlying data point or to remove it. Data scientists need to be able to detect outliers. … Read more

Linear and Nonlinear Models in Machine Learning

Linear and Nonlinear Models in Machine Learning

Linear and nonlinear models are two types of classification models used in machine learning. A linear model plots features and their associated outcomes on a hyperplane. Nonlinear models are more complex and do not have a straightline – they have complex boundaries. A neural net is an example of a nonlinear modeling. This classifier uses … Read more

What Is Feature Scaling Machine Learning?

Feature Scaling In Machine Learning

ML features scaling is an important aspect of ML. Small datasets allow a model to learn better than large ones, since the range of numerical values is smaller. Feature scaling is necessary for any model that computes distances, such as linear regression and logistic regression. It is also necessary for other models, such as SVM, … Read more

Best Desktop PC for Machine Learning

Best Desktop PC for Machine Learning

Which is the best desktop PC for machine learning? It all depends on your needs, your budget, and your expectations. High computing power is required to make a computer suitable for deep learning. You should opt for a GPU with plenty of memory, a processor with a lot of cores, and plenty of RAM. In … Read more

What is Data Normalization in Machine Learning (ML)?

What is Data Normalization in Machine Learning

In the context of machine learning, data normalization is an essential process for ensuring a more accurate prediction. It helps organizations make the best use of their datasets by consolidating and querying data from multiple sources. The main benefits of this process are cost savings, space savings, and accuracy improvements. The exact steps and benefits … Read more

Choosing the Best Server for Machine Learning

Best Server for Machine Learning

When building a data science workflow for machine learning, you need a server that can support a large number of machines and offers low-latency modeling. Fortunately, the best servers can handle the vast majority of machine learning workloads. A model server that supports Python is a great choice, but other languages have their supporters. These … Read more

XGBoost Text Classification

XGBoost Text Classification

XGBoost is a powerful tool for text classification. It allows you to automatically create and analyze a classifier for a variety of different datasets. Using the TF-IDF model, you can categorize data in a variety of ways. Its XGBoost algorithm is able to distinguish between different categories and improve classification accuracy. XGBoost is much easier … Read more

Machine Learning and Bayesian Reasoning

Machine Learning and Bayesian Reasoning

Machine learning and Bayesian reasoning are two widely used algorithms for extracting value from huge data sets with a modest amount of resources. These techniques have been used in a wide range of industrial applications, including search engines, DNA sequencing, and stock market analysis. The applications for these techniques are growing exponentially. These techniques have … Read more

What is Multi Label Classification?

What is Multi Label Classification

Multi-label classification uses an image to assign labels for different items. These labels can be objects, people, concepts, or both. This technique is also used in bioinformatics, and other related areas. For example, this technique is used to classify yeast genes and predict multiple functions for proteins. For example, Google News categorizes all news articles … Read more