How to Raise Accuracy in Keras Neural Network from 44% to 80%
Improving accuracy in your Keras neural network is essential for building robust machine learning models. To raise accuracy, start by preprocessing your data effectively, normalizing and scaling features to ensure consistency. Experiment with different network architectures,…
How to Prepare Data with a Lot of Outliers for Machine Learning
In the realm of machine learning, data preparation plays a crucial role in developing accurate and reliable models. However, when faced with a dataset containing a large number of outliers, the task of preparing the data…
Predicting Heart Disease in Patients Using Machine Learning Methods
Heart disease remains one of the leading causes of mortality worldwide, accounting for millions of deaths annually. Early detection and accurate prediction of heart disease are critical for effective prevention and timely medical intervention. With the…
Forecasting House Prices with Sklearn
Sklearn is a popular open-source machine learning library in Python that provides a wide range of tools for classification, regression, clustering, and more. It offers numerous algorithms and pre-processing techniques that can be leveraged to create…
Building Models in Python and Assessing Them Using ROC Curve and Precision-Recall Curve
When it comes to building predictive models in Python, it is crucial to evaluate their performance thoroughly. Two widely used evaluation metrics are the ROC curve and the Precision-Recall curve. These curves provide valuable insights into…
Creating Gradient Descent Models in Pure Python
In the field of machine learning, gradient descent is a widely used optimization technique that helps us find the optimal parameters for our models. While there are numerous libraries available to implement gradient descent, such as…
Building Machine Learning Models for Predicting People’s Income
Machine learning has become an indispensable tool in today’s data-driven world. With the ability to analyze vast amounts of data, it has made predictions and classifications more accurate and efficient. One area where machine learning has…
Building a Neural Network for Classifying Movie Reviews
Building a neural network for classifying reviews is a complex yet crucial task in the realm of sentiment analysis. The process involves the construction of a multi-layered interconnected network of artificial neurons that can learn patterns…
Analysis of online cinema data and building a recommender system
Nowadays, many online movie theaters face a number of challenges, such as intense competition, lack of quality content, high advertising costs, and difficulty retaining customers. Big data analysis and machine learning can help solve these problems.…
Image Recognition with Keras Neural Networks
Image recognition with Keras neural networks has emerged as a cutting-edge technology in the field of computer vision. As a deep learning framework, Keras offers a high-level interface for building and training convolutional neural networks (CNNs)…
Handwritten Number Recognition with Neural Networks
Computers can recognize images through a process called image recognition or computer vision. At the heart of this technology lies deep learning algorithms, specifically convolutional neural networks (CNNs), which mimic the human brain’s processing of visual…
Predicting cellular company Churn with ML and PySpark
The business model of the vast majority of cellular companies on Earth is built on the long term – regular monthly payments from customers. This model is also called LTV. The risk of subscriber outflow for…
Predicting bank customer Churn with 99.9% Accuracy
Every bank wants to retain as many of its customers as possible to sustain its business. Because it costs a lot more to bring in a new customer than it does to retain an existing one.…
Building Simple Machine Learning Models in PySpark
PySpark is a powerful data processing tool that allows you to analyze large-scale datasets in parallel. It’s an Apache Spark library in Python, designed to work with Big Data on systems such as Hadoop Distributed File…
Predicting Diabetes using Machine Learning
People get diabetes for a variety of reasons. Genetics can play a role in the development of diabetes, but lifestyle factors are also significant contributors. A diet high in processed foods and added sugars, lack of…
