Category: Machine Learning
Language 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 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 MoreWhat is the ROC curve?
The ROC curve is a graph between False positive rate on the x axis and True positive rate on the y axis. True positive rate is the ratio of True positives to the total number of positive samples. False positive rate is the ratio of False positives to the total number of negative samples. The…
Read MoreWhat do you understand by true positive rate and false-positive rate?
True Positive rate (TRP) is the ratio of True Positives to True Positives and False Negatives. It is the probability that an actual positive will test as positive. TPR = TP / TP + FN The False Positive Rate (FPR) is the ratio of the False Positives to all the positives (True positives and false…
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