Build a Music Recommendation system.
Train machine learning algorithms to detect Breast Cancer
Train machine learning algorithms to predict Diabetes
Automated Malaria detection using deep learning models like CNN
Bitcoin price prediction using machine learning
Series Prediction with LSTM Recurrent Neural Networks
Artificial intelligence, Data science, Machine learning, Deep learning projects
Requirements:
Should Know Basics of Machine Learning
Should Know about Machine Learning Libraries
A passion to learn data science
Jupyter notebook
Description:
Machine learning (ML) is a branch of artificial intelligence (AI) that enables computers to self-learn and improve over without being explicitly programmed. In short, machine learning algorithms are able to detect and learn from patterns in data and make their own predictions.
In traditional programming, someone writes a series of instructions so that a computer can transform input data into a desired output. Instructions are mostly based on an IF-THEN structure: when certain conditions are met, the program executes a specific action.
Machine learning, on the other hand, is an automated process that enables machines to solve problems and take actions based on past observations.
Basically, the machine learning process includes these stages:
Feed a machine learning algorithm examples of input data and a series of expected tags for that input.
The input data is transformed into text vectors, an array of numbers that represent different data features.
Algorithms learn to associate feature vectors with tags based on manually tagged samples, and automatically makes predictions when processing unseen data.
While artificial intelligence and machine learning are often used interchangeably, they are two different concepts. AI is the broader concept - machines making decisions, learning new skills, and solving problems in a similar way to humans - whereas machine learning is a subset of AI that enables intelligent systems to autonomously learn new things from data.
In this course, we are going to provide students with knowledge of key aspects of state-of-the-art classification techniques. We are going to build 8 projects from scratch using real world dataset, here's a sample of the projects we will be working on:
Build a Music Recommendation system.
Human activity recognition using smartphones
Series Prediction with LSTM Recurrent Neural Networks
Predicting presence of Heart Diseases using Machine Learning
Automated malaria detection using deep learning models like CNN
Predicting Prices of Bitcoin with Machine Learning
Breast Cancer Prediction using Machine Learning
Predicting Diabetes With Machine Learning Techniques
Who this course is for:
Bner in machine learning
Want to build real world machine learning projects






DOWNLOAD
uploadgig.com


rapidgator.net


nitro.download