Any dataset used in Machine Learning algorithms may have a number of dimensions. However, not all of them contribute to giving an efficient output and simply cause the ML Model to perform poorly because of the increased size and complexity. Thus, it becomes important to eliminate such features from the dataset. To do this, we use a dimension reduction algorithm called PCA. PCA or Principal Component Analysis helps in removing those dimensions from the dataset that do not help in optimizing the results; thereby creating a smaller and simpler dataset with most of the original and useful information. PCA is ... Read More

Recommendation system is a tool in python that suggests items or content to users based on their preferences and past behaviors. This technology utilizes algorithms to predict users' future preferences, thereby providing them with the most relevant content. The scope of this system is vast, with widespread use in various industries such as e-commerce, streaming services, and social media. Products, movies, music, books, and more can all be recommended through these systems. The provision of personalized recommendations not only helps foster customer engagement and loyalty but can also boost sales. Types of Recommendation Systems Content-based recommendation systems These operate on ... Read More

Support Vector Machines (SVMs) are supervised learning algorithms that can be used for both classification and regression tasks. SVMs are powerful algorithms that can be used to solve a variety of problems. They are particularly well−suited for problems where the data is linearly separable. However, SVMs can also be used to solve problems where the data is not linearly separable by using a kernel trick. In this article, we will explore the theory behind SVMs and demonstrate how to implement them for data classification in Python. We will provide a detailed explanation of the code, and its output, and discuss ... Read More

Neural Network is a widely used concept in the field of Artificial Intelligence and is based on the structure of the human brain. A neural network works in layers, the simplest one being a sequential model where the input of the current layer is the output of the previous layer. To create, train and test a neural network model, we can use a deep learning framework like Tensorflow in Python. Every neural network model is based on a few simple steps like taking data, making predictions, comparing predictions and finally, changing them to go closer to the target. ... Read More

Machine learning is one of the branches of artificial intelligence that involves developing Statistical models and algorithms that can enable a computer to learn from the input data and make decisions or predictions without being hard programmed. It involves training the ML algorithms with large datasets so that the machine can identify patterns and relationships in the data. What is an Autoencoder? Neural network architectures with autoencoders are used for unsupervised learning tasks. It is made up of a network of encoders and decoders that have been trained to rebuild the input data by compressing it into a lower-dimensional representation ... Read More

If you have ever talked with chatbots and used language translation tools, then you will know that these tools work exactly like a real human. This is possible because they use Natural Language Processing (NLP) techniques to understand the natural languages that humans use for communication. However, this is quite complex because each language has a different nature and structure along with various contexts. Natural Language Processing (NLP) uses a number of techniques to get outputs as close as the natural language. Some of these techniques include − Lemmatization − It is the process that reduces the ... Read More

Naive Bayes algorithm is a powerful tool that one can use to classify the words of a document or text in different categories. As an example, if a document has words like ‘humid’, ‘rainy’, or ‘cloudy’, then we can use the Bayes algorithm to check if this document falls in the category of a ‘sunny day’ or a ‘rainy day’. Note that the Naive Bayes algorithm works on the assumption that the words of the two documents under comparison are independent of each other. However, given the nuances of language, it is rarely true. This is why the algorithm’s ... Read More

Using NMT or Neural Machine Translation in NLP, we can translate a text from a given language to a target language. To evaluate how well the translation is performed, we use the BLEU or Bilingual Evaluation Understudy score in Python. The BLEU Score works by comparing machine translated sentences to human translated sentences, both in n-grams. Also, with the increase in sentence length, the BLEU score decreases. In general, a BLEU score is in the range from 0 to 1 and a higher value indicates a better quality. However, achieving a perfect score is very rare. Note that the ... Read More

Introduction In Python programming, merging sublist elements from two diverse records could be a common operation when managing with complex information structures. The capacity to combine sublist components productively is vital for assignments such as information control, examination, and visualization. This article investigates three prevalent approaches to combining sublist components in Python, giving step−by−step clarifications, code illustrations, and comparing yields for each approach. The article starts by presenting the significance of consolidating sublist components and its pertinence in different programming scenarios. It emphasizes the importance of understanding diverse calculations and strategies to productively consolidate sublists from diverse records. Python−Merge ... Read More

Introduction Python, now widely regarded as one of the most versatile programming languages, offers a plethora of built−in functions and methods that simplify complex tasks. In this article, we dive into finding the maximum and minimum values among two Python lists rapidly using these native capabilities. Whether we are a beginner or an experienced programmer, understanding how to leverage these functionalities can significantly streamline our code. Finding the Maximum and Minimum values from two Python lists Before we explore how to find max and min values from two separate lists, let's first familiarize ourselves with the respective functions provided by ... Read More