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Machine Learning (ML) technology is the process of making machines more human-like in their behavior. It helps them to take decisions by themselves. Machine learning can apply to a large number of industries and applications also. This makes them more efficient and also intelligent. Today it is an essential skill for all ambitious data analysts and data scientists. So, if you are a beginner, the most important thing you need to do is choose some best Machine Learning Project Topics and work on them. Project based learning make students industry ready.
Machine learning is very much important nowadays. In fact the main reason is that it can solve real-world problems which are complicating for humans. For all businesses, data is their lifeblood. Therefore data-driven decisions are important for business organizations. Machine learning can also be an important factor for businesses in analyzing customer data. Thus they can take crucial decisions that keep company ahead of the competition.
Pantech eLearning Chennai is an Online Learning Service provider. We are providing some latest Project Topics on Machine Learning. The Machine Learning Project Topics will help you to learn and understand the technology deeply to build a successful career.
Given below is the Top 10 Machine Learning Project Topics we are providing:
In this project, we came up with a framework through which we can detect a fake profile using machine learning algorithms so that the social life of people becomes secure.
The intention of this project is to discuss a novel approach of hand gesture recognition depends on detection of some shape base features.
After surveying the previously use factors for predicting the student’s academic performance, we pick the most relevant attributes based on their rationale and also correlation with the academic performance.
Models for prediction of water table depth were developed depends on Artificial Neural Networks (ANN) with different combinations of hydrological parameters.
Here we collect all the twitter data. Using the data we extract all the future and getting more numbers data’s also. So we apply the Logistic regression model to classify the values and we get the more accuracy score like above 80%.
This Project comes up with the applications of Random Forest techniques for detecting the fake misleading news stories that comes from the non-reputable sources.
In our project, proposed system is accuracy prediction of heart disease problem in health care application. Easier to analyze the scalability of health care big data and also less time consumption with efficiency of data in heart disease.
The paper proposes a workflow for the automatic detection of anomalous behaviour in an examination hall, towards the automated proctoring of tests in classes.
Intrusion detection system (IDS) is a system that monitors and analyzes data to detect any intrusion in the system or network. This project also introduce Spark‑Chi‑SVM model for intrusion detection.
This aims to classify textual content into non-hate or hate speech, in which case the method may also identify the targeting characteristics (i.e., types of hate, such as race, and religion) in the hate speech.
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