Maddali

Gain insight into the fundamental processes involved in building a decision tree classifier from the groundPhoto by Jeroen den Otter on UnsplashDecision trees serve various purposes in machine learning, including classification, regression, feature selection, anomaly detection, and reinforcement learning. They operate using straightforward if-else statements until the tree’s depth is reached. Grasping certain key concepts is crucial to fully comprehend the inner workings of a decision tree.Two critical concepts to grasp…

With the aid of convolutional neural networks and transfer learning, it is possible to build a classifier in determining whether solar panels are clean or dustyPhoto by Moritz Kindler on UnsplashSolar panels have become a popular source of renewable energy in a variety of industries, from agriculture and transportation to construction and hospitality. By harnessing the power of the sun, we can generate electricity without harming the environment. However, there are challenges associated with using solar panels, and one of…

Build an article recommender system with unsupervised machine learning and generate features and patterns that aid in the recommendationPhoto by Salomé Watel on UnsplashThere have been a lot of talks lately about the incredible capabilities of artificial intelligence and machine learning. As we go on to see various frontiers at which ML could be applied, there is a growing possibility of higher value generated as a result of this transition. Companies such as Google, Microsoft, and NVIDIA are pushing the boundaries at…

Learn the right feature engineering techniques when applied to credit card fraud detection problem that improves the overall accuracy of machine learning modelsPhoto by Tierra Mallorca on UnsplashMachine learning and data science are used in a large number of industries. One of the most popular applications of data science is in the field of finance. A lot of companies are trying to automate tasks such as whether to give loans to lenders or not to whether a transaction is fraudulent or non-fraudulent. In addition to this,…

Learn how machine learning could be used to analyze audio signals and generate predictions for both classification and regression tasksPhoto by Jarrod Reed on UnsplashMachine learning has been gaining rapid traction in the recent decade. In fact, it is being used in numerous industries such as healthcare, agriculture, and manufacturing. There are a lot of potential applications of machine learning being created with the advancement of technology and computational power. Since data is available in various formats in…

Learn various deployment strategies for successfully building an end-to-end machine learning pipelinePhoto by Jiawei Zhao on UnsplashThere is a lot of scope and demand for machine learning, especially in the latest self-driving industry where drivers are given assistance with the aid of AI. Furthermore, there are other industries benefiting such as the pharmaceutical industry that are beginning to use AI in building interesting products that are essentially used for predictive healthcare. Other industries include…

OpinionUnderstanding the occurrence of various mistakes in data science, especially when building machine learning code is useful for practitioners of data science and artificial intelligence. In this article, we would be exploring steps to avoid these mistakes and improve productivity.Photo by Jan Antonin Kolar on UnsplashMachine learning and data science are being used in a wide variety of applications. Some of the cool applications of machine learning are in self-driving cars and also in banking industries of whether a…

Understanding the various feature engineering techniques can be handy for an ML practitioner. After all, features are one of the most determining factors about how machine learning and deep learning models perform in real-time.Photo by Alain Pham on UnsplashWhen it comes to machine learning, the thing that one can do to improve the ML model predictions would be to choose the right features and remove the ones that have negligible effect on the performance of the models. Therefore, selecting the right features can be one…

Learn how to build interesting pipelines in the field of machine learning to develop a system that can perform AI capabilitiesPhoto by 夜 咔罗 on UnsplashOftentimes we are asked in either interviews or in our job roles as data scientists to build an application that is capable of performing machine learning predictions for continuous streaming data. There is often expectation from our boss that we are going to be delivering the results on time and generate these high-quality predictions with the use of machine learning and…

Understanding various ways at which machine learning projects fail ensures that one takes the right steps and measures to avoid them before facing the situationPhoto by CHUTTERSNAP on UnsplashOkay, you did a good job in ensuring that your machine learning model is doing well on the training data. The next step would be to deploy it in real-time and get feedback from users and from the business about whether using it has led to an increase in the revenue of various data products. But for a successful machine learning…