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Master Artificial Intelligence by Building 12 Machine Learning & Deep Learning Projects with Python (2021)

What you'll learn
You will practice Machine Learning and Deep Learning Algorithms by solving real life problems using latest version of libraries (July 2021)
How to use Machine Learning and Deep learning algorithms in different difficulty level projects using Python
NLP (Natural Language Processing) Implementation using Python
Image Classificiation Implementation using Deep Learning
Time Series Prediction Implementation suing Python and Keras Tensorflow
Clustering, Regression and Classification Algorithms Implementation using Python
All 11 downloadable projects include Python source code that is composed of Machine Learning & Deep Learning Algorithms and models
IMDB Sentiment Analysis using Machine Learning
Transfer Learning Implementation using InceptionResNetV2
Artificial Neural Networks Implementation using Python
Well known datasets used in Artificial Intelligence education

Description
Welcome,

In this course, we aim to specialize in artificial intelligence by doing Machine Learning and Deep Learning Projects at various levels. Before starting the course, you must 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.

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.

In our Deep Learning projects we will use the latest version of Tensorflow and Keras libraries.

Our course consists 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 Image Classification using Deep Learning (VGG16 & 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 скачать source codes for all projects..

Who this course is for:
Everyone who is interested in Artifical Intelligence
Everyone who is interested in Machine Learning, Deep Learning and Artificial Neural Networks
Everyone who is interested in NLP
Everyone who is interested in Machine Learning and Deep Learning

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Homepage
https://www.udemy.com/course/deep-learn … on-course/

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