Author: Naveen
Naveen PandeyWhat is object detection?
Machine Learning is a powerful, but often misunderstood technology. It’s best known for its applications in the computer vision field, but can be applied to any industry. One of the more common uses is for automatic pedestrian and car detection in footage from surveillance systems and factory video feeds. Object detection is a deep learning…
Read MoreHow Instagram uses Machine Learning
Instagram is one of the most popular social media applications today. As with any business today, there are many areas where Instagram uses data science. So, if you want to know how Instagram uses Machine Learning, this article is for you. In this article, we’ll take a look at some of the ways Instagram uses machine learning. Below are some of the ways Instagram is using data science for their business. Instagram…
Read MoreAutomatic Number Plate Recognition Project
In recent years, automatic license plate recognition or license plate recognition has become one of the useful approaches for vehicle surveillance. This article presents an automatic license plate recognition project using OpenCV and EasyOCR. Traffic control and vehicle owner identification have become major problems in all countries. It can be difficult to identify the owner of a speeding vehicle that violates the road rules. Therefore, due to the speed of the vehicle, traffic personnel may not be able to obtain the vehicle number of the moving vehicle, so such…
Read MoreLanguage Detection Project using Machine Learning
Speech recognition is a natural language processing task that requires identifying the language of a text or document. Using machine learning for speech recognition was a difficult task a few years ago due to the lack of much data on language, but now that data is readily available, several powerful machine learning models are already available. So, if you want to learn how to train machine learning models for speech recognition, this article is for you. This…
Read MoreCounting Objects in An Image
Counting objects in an image is the job of computer vision. There are many Python computer vision libraries available for this task. However, this article describes a very simple approach to counting objects in images using Python. How to count objects in an image using Python? Counting objects in an image is a computer vision task. There are many image processing libraries available for this task. B. OpenCV, TensorFlow, PyTorch, Scikit-image, and cvlib. You probably haven’t heard much about Python’s cvlib library. This is a very simple, advanced, and easy-to-use…
Read MoreProduct Demand Prediction Project Using Machine Learning
You must have learned that demand for a product change as the price of the product changes. To give a real-life example, if a product is not needed, demand decreases when price increases, and demand increases when price decreases. If you want to know how to use machine learning to predict product demand, this article…
Read MoreCalories Burnt Prediction Project using Machine Learning
In this article, we will learn how to develop a machine learning model using Python which can predict the number of calories a person has burnt during a workout based on some biological measures. You can download Calories dataset from here and Exercise dataset from here. we will import all the necessary libraries and also warnings which we take care…
Read MoreExplanation for AI and Data Science by ChatGPT AI
Question to ChatGPT: Explain AI Artificial intelligence (AI) is the ability of a computer program or a machine to simulate human intelligence, including the ability to reason, learn, and solve problems. AI can be applied to a wide range of field, including robotics, natural language processing, computer vision, and machine learning. The goal of AI…
Read MoreImportant Machine Learning Concepts Part – 2
Ensemble Learning Training multiple models with different parameters to solve the same problem. A/B Testing Statistical way of comparing 2+ techniques to determine which technique performs better and also if difference in statistically significant. Baseline Model Simple model/heuristic used as reference point for comparing how well a model is performing. Bias Prejudice or favourite towards…
Read MoreImportant Machine Learning Concepts Part – 1
Features Input data/variables used by the ML model. Feature Engineering Transforming input features to be more useful for the models. e.g., mapping categories to buckets, normalizing between -1 and 1, removing null. Train/Eval/Test Training is data used to optimize the model, evaluation is used to asses the model on new data during training, test is…
Read MoreWhat is selection Bias?
Selection bias is a kind of error that occurs when the researcher decides who is going to be studied. It is usually associated with research where the selection of participants isn’t random. It is sometimes referred to as the selection effect. It is the distortion of statistical analysis, resulting from the method of collecting samples.…
Read MoreWhat is a confusion matrix?
The confusion matrix is a 2×2 table that contains 4 outputs provided by the binary classifier. Various measures, such as error-rate, accuracy, specificity, sensitivity, precision and recall are derived from it. Confusion matrix. A dataset used for performance evaluation is called a test data set. It should contains the correct labels and predicted labels. The…
Read MoreFeatured Articles
-
Zero to Python Hero – Part 5/10: Essential Data Structures in Python: Lists, Tuples, Sets & Dictionaries
-
Top 5 Skills Every Engineer Should Learn in 2026
-
Zero to Python Hero - Part 4/10 : Control Flow: If, Loops & More (with code examples)
-
Zero to Python Hero - Part 3/10 : Understanding Type Casting, Operators, User Input and String formatting (with Code Examples)
-
Dynamic Programming in Reinforcement Learning: Policy and Value Iteration
Latest Articles
-
Zero to Python Hero – Part 6/10: Functions and Modules in Python
-
Zero to Python Hero – Part 5/10: Essential Data Structures in Python: Lists, Tuples, Sets & Dictionaries
-
Top 5 Skills Every Engineer Should Learn in 2026
-
Zero to Python Hero - Part 4/10 : Control Flow: If, Loops & More (with code examples)
-
Zero to Python Hero - Part 3/10 : Understanding Type Casting, Operators, User Input and String formatting (with Code Examples)
-
Zero to Python Hero - Part 2/10 : Understanding Python Variables, Data Types (with Code Examples)
