Artificial Intelligence Projects with Python

Artificial Intelligence Projects with Python

Artificial Intelligence Projects with Python

Artificial Intelligence Projects with Python

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Master Artificial Intelligence by Building 12 Machine Learning & Deep Learning Projects with Python (2021), Course content · Introduction3 lectures • 17min · Project # 1: House Price Prediction using Machine Learning3 lectures • 12min · Project #2: HR Salary Calculation Fake Currency Detection with Machine Learning. PredictTinder Matches with Machine Learning. ... Title Generator with Python. Pencil Sketch with .Created by Yazılım Teknolojileri Akademisi



Description Artificial Intelligence Projects with Python

In this course, we aim to specialize in artificial intelligence by working on 12 Machine Learning and Deep Learning Projects at various levels. Before starting the course, you should have basic Python knowledge. Our aim in this course is to turn real-life problems that seem difficult to do into projects and then solve them using latest versions of artificial intelligence algorithms and Python(3.8). This course was prepared in July 2021.
We will carry out some of our projects using machine learning and some using deep learning algorithms. In this way, you will have a general perspective on artificial intelligence. When you complete the projects in our course, you will get a clear understanding of the basic working principles of Machine Learning software and Deep Learning algorithms and the difference between them.
In our course, we will use well known datasets that are widely used by high level education about Machine Learning as well as custom datasets. By doing our projects, you will master artificial intelligence concepts as well as learn these famous datasets. After completing the course, you will be able to easily produce solutions to the problems that you may encounter in real life.
In our Machine Learning Projects we will use Scikit-Learn Python library. In our Deep Learning Projects we will use Tensorflow and Keras libraries.
The course is composed of 12 Artificial Intelligence (Machine Learning & Deep Learning) Projects:
Project #1: House Price Prediction using Machine Learning
Project #2: HR Salary Calculation using Machine Learning
Project #3: Handwritten Digit Recognition using Multiple Machine Learning Models
Project #4: Advanced Customer Segmentation using Machine Learning
Project #5: IMDB Sentiment Analysis Using NLP (Natural Language Processing)
Project #6: Building a Movie Recommendation System
Project #7: Predicting Diabetes using Artificial Neural Networks
Project #8: Image Classification using Convolutional Neaural Network and Artificial Neural Network Algorithms (Deep Learning)
Project #9: Airline Passenger(Time Series) Prediction using Keras LSTM (Deep Learning)
Project #10: San Francisco Crime Geographical Clustering using Machine Learning
Project #11: Image Classification (ImageNet Library) using Transfer Learning - Keras InceptionResNetV2 (Deep Learning)
Project #12: Military Aircraft (Satellite Imagery) Classification using Deep Learning (Custom Datasets)
Each project will be implemented by Python using Jupyter Notebook. Python source code of each project is included in relevant Udemy course section. You can download source codes for all projects..

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Machine learning is the study of computer algorithms that improve automatically through experience and by the use of data. It is seen as a part of artificial intelligence. Machine learning algorithms build a model based on sample data, known as "training data", in order to make predictions or decisions without being explicitly programmed to do so. Machine learning algorithms are used in a wide variety of applications, such as in medicine, email filtering, speech recognition, computer vision and defence industry where it is difficult or unfeasible to develop conventional algorithms to perform the needed tasks.
Deep learning is a class of machine learning algorithms that uses multiple layers to progressively extract higher-level features from the raw input. For example, in image processing, lower layers may identify edges, while higher layers may identify the concepts relevant to a human such as digits or letters or faces. Deep learning is part of a broader family of machine learning methods based on artificial neural networks with representation learning. Deep learning is an artificial intelligence function that aims to imitate the human brain’s ability to process data and recognise patterns for learning and making decisions.

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