Naveen Pandey has more than 2 years of experience in data science and machine learning. He is an experienced Machine Learning Engineer with a strong background in data analysis, natural language processing, and machine learning. Holding a Bachelor of Science in Information Technology from Sikkim Manipal University, he excels in leveraging cutting-edge technologies such as Large Language Models (LLMs), TensorFlow, PyTorch, and Hugging Face to develop innovative solutions.
Blockchain technology has the potential to improve machine learning by providing a decentralized platform to collect, store and analyze data in a secure and transparent manner. This means that data cannot be tampered with or changed without the owner’s permission, making machine learning algorithms more accurate and stable. One of the main advantages of blockchain…
The blockchain is a revolutionary technology which has the potential to change how we do business. It can be used in many different fields and industries, but one of the most interesting applications is in Natural Language Processing. The blockchain has the potential to revolutionize how data is stored and shared. It can store data…
The media industry is one of the most competitive industries today. The competition is so fierce that it has forced companies to come up with new ways of attracting their audience. One way they have been able to do this is by adding visual content to their articles. The use of image processing software has…
Image processing has been widely used in the medical industry for a variety of purposes. The most common use cases are diagnosis, treatment and image archiving. Machine vision in healthcare is a way to process medical data. It is a way for doctors to get more information about their patients. Machine vision in healthcare can…
Every day, a computer vision system processes millions of photos, videos and other media. Progress in computational power and deep learning has led to major advances in the field of computer vision. These advancements have created new opportunities for computer vision that we can explore today. The 5 popular Machine learning algorithm in computer vision…
Computer vision is an emerging technology that is being used in medical fields for many applications. Some of the applications include imaging, point of care diagnostic testing and diagnosing diseases, surgical interruption, surgical navigation and analysis of MRI images. The technology has been used to automate many healthcare procedures like Triage and Augmented Reality surgery.…
Computer vision is the ability of a computer to understand its environment by analyzing the images it captures. It has applications in many industries such as agriculture, manufacturing. In agriculture, computer vision is used for tasks such as crop classification, disease detection, pest identification, and weed recognition. This article will focus on some of the…
Image processing is a technique that captures, analyzes, and modifies images. It is widely used in various fields like medical imaging, remote sensing and digital photography. OpenCV is a free open-source library that gives you access to algorithms for all the computer vision and image processing procedures you might need. It is not just a…
The technology behind face recognition is called computer vision. Computer vision is the science and technology that deals with how computers can be programmed to understand images and video in order to process them in some way. It is a branch of artificial intelligence that focuses on giving machines the ability to see, just as…
Semi-supervised learning is a technique in between supervised and unsupervised learning. Arguably, it should not be a category of machine learning but only a generalization of supervised learning, but it’s useful to introduce the concept separately. Its aim is to reduce the cost of gathering labelled data by extending a few labels to similar unlabeled…
One of the most common problems in RNNs is called gradient vanishing. LSTM architectures help you with this. A very common type of RNN is LSTM. This type of network is much better at capturing long-term dependencies than simple RNNs. The only unusual thing about LSTMs is the way that they compute the hidden state.…
Recurrent neural network is a type of deep learning algorithm which is used to process sequential data. The main idea of recurrent neural network is that it can learn from previous information and then use that information to predict the next one. That’s why it’s called a recurrent neural network, because it can go back…