Tag: Machine_Learning
Creating Pickle files in Python: A step-by-step guide
Creating a Pickle file in Python is a straightforward process. It involves serializing a Python object (like a machine learning…
Pickle vs HDF5: Comparing model storage formats [.pkl or .pickle , .h5 or .hdf5 ]
When it comes to saving machine learning models, two common file formats are Pickle files (typically with .pkl or .pickle…
Pickling in Machine Learning – A brief overview
In machine learning, “pickling” refers to the process of serializing and saving a model in a persistent state. Serialization is…
SHAP Plot in Data Science an overview with fundamentals
In the world of machine learning, model interpretability is paramount. While black-box models, such as deep neural networks or ensemble…
KS (Kolmogorov-Smirnov) Plot in Data Science
KS Plot in Data Science Introduction The Kolmogorov-Smirnov (KS) statistic is a non-parametric test used to compare a sample distribution…
Strategies and tips for managing bad or missing data
Here we are explaining for two scenario : Machine Learning and ETL Machine Learning Data is the linchpin of modern…
Benefits of using Convolutional Neural Networks (CNNs) in Facial Emotion Recognition (FER)
Convolutional Neural Networks (CNNs) have demonstrated exceptional performance in tasks related to Facial Emotion Recognition (FER). Here are several benefits…
Over view of classification_report tool in machine learning
classification_report is a commonly used tool in machine learning for evaluating the performance of classification algorithms. It provides a detailed…
Understanding Precision, Recall, and F1-Score in Classification Metrics
Precision, recall, and F1-score are crucial metrics in the context of classification problems, particularly when classes are imbalanced or when…
Training Neural Networks with Keras: Understanding the fit Method
The cnn.fit method in Keras is used to train the model. Here’s a simple breakdown: Training the Model: The main…
