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Python is a popular programming language that is widely used in data science, machine learning, and other fields. One of the reasons for its popularity is the availability of powerful libraries such as Matplotlib, which allows users to create high−quality visualizations with ease. Matplotlib is a popular data visualization library in Python that provides a wide range of tools for creating different types of plots, including scatter plots. In this tutorial, we will explore how to connect scatterplot points with a line in Matplotlib. Scatter plots are useful for visualizing the relationship between two variables, and adding a line to ... Read More
Building modern web applications that are both scalable and engaging requires the use of relevant technologies. ReactJS and Flask are two popular frameworks that are commonly used for front−end and back−end development respectively. In this article, we'll explore the process of connecting ReactJS with Flask API to create robust web applications that take advantage of the unique features offered by both technologies. We'll provide you with a step−by−step guide on how to set up a Flask API, enable Cross−Origin Resource Sharing (CORS), make API requests from ReactJS, display the API data in the user interface, and handle API errors. ... Read More
MySQL is an open−source relational database management system that is widely used to store, manage, and organize data. When working with MySQL tables, it is common to require the combination of multiple column values into a single string for reporting and analysis purposes. Python, a high−level programming language, offers several libraries that enable connection to MySQL databases and execution of SQL queries. In this article, we'll dive into the process of concatenating column values of a MySQL table using Python and the PyMySQL library. A step−by−step guide is provided on how to connect to a MySQL database, execute a SQL ... Read More
A simultaneous perturbation stochastic optimization algorithm (SPSA) finds the minimum of an objective function by simultaneously perturbing the objective function. Using SPSA, the objective function gradient is estimated by evaluating a small number of functions at random perturbations. It is particularly useful when the objective function is noisy, non-differentiable, or has many parameters. A variety of applications, such as system identification, control, and machine learning, have been successfully implemented with this algorithm. Advantages Of Using The SPSA Algorithm The SPSA has been applied in various realms such as engineering, finance, and machine learning. It has several advantages ... Read More
The original Titanic project in Machine learning is aimed at finding whether a person on the Titanic will survive or not. However, this project named the spaceship Titanic is a bit different. The problem statement here is that a spaceship has people going on a trip in space. But due to a collision, a few people need to be transported to some other dimension or planet. Now this can’t be done randomly. So, we will use a Machine Learning technique in Python to find out who will get transported and who will not. Algorithm Step 1 − ... Read More
In Java, every interface, class, object, variable and method of a running program is stored in distinct reasons of computer memory. The heap is the part of memory area where values of variables, methods and classes are stored at runtime. Its allocation happens dynamically and can grow or shrink depending on the application's needs. On the other hand, the reference variables, names of methods and classes are stored in the stack memory area. However, if for some reason their allocation is not handled properly then, it may lead to memory errors that we are going to discuss in this article. ... Read More
Early detection of any disease, especially cancer, is very crucial for the treatment phase. One such effort made in this direction is the use of machine learning algorithms to detect and diagnose skin cancer with the help of a machine learning framework like Tensorflow. The traditional method of cancer detection is quite time-consuming and requires professional dermatologists. However, with the help of TensorFlow, not only can this process be made fast, but more accurate and efficient. Moreover, people who do not get timely access to doctors and dermatologists, can use this meanwhile. Algorithm Step 1 − Import the ... Read More
The power of machine learning has enabled us to predict rainfall with several algorithms, including Random Forest and XGBoost. There are no best algorithms for predicting rainfall, every algorithm has its advantages and disadvantages. The Random Forest is efficient with small datasets, while the XGboost is efficient with large datasets. In the same way, we can categorise other algorithms based on the needs of our projects. Our goal here is to build a predictive machine-learning model of rainfall based on Random Forests. Algorithm Import all the required libraries such as Pandas, Numpy, Sklearn, and matplotlib. Load the ... Read More
Like in many other sectors, predictive analysis is quite helpful in the finance and insurance sector as well. Using this machine learning technique, we can find out useful information about any insurance policy and therefore save huge sums of money. Here, we will be using this approach of predictive analysis for a medical insurance dataset. The problem statement here is that we have a dataset of some people with certain attributes. Using machine learning in Python, we have to find out relevant information from this dataset and also have to predict the insurance price a person will have to ... Read More
Machine learning is a subset of artificial intelligence (AI) that enables machines to learn from data without being explicitly programmed. From predicting customer behavior to recognizing images and speech, it is a rapidly growing field. Adding machine learning to your toolkit can help you excel in many sectors such as finance, fraud detection, automobile, research, etc. Day 1-5: Basics of Machine Learning Before diving into its technical aspects, it is imperative to understand the fundamental concepts of machine learning. Learn about the types of machine learning, such as supervised, unsupervised, and reinforcement learning. Focus on key points, ... Read More