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Artificial neural networks (ANNs) are the most powerful machine learning algorithms available today. They are capable of learning complex relationships in data, and they have been used to achieve state-of-the-art results in a wide variety of fields, including image recognition, natural language processing, and speech recognition. The Future of Machine Learning is Here! This Project on Deep Learning - Artificial Neural Network course will teach you how to build and train ANNs from scratch. You will learn about the different components of an ANN, such as the input layer, hidden layers, and output layer. You will also learn about the different activation functions that can be used in ANNs, and you will see how to optimise ANNs for different tasks. In addition to the theoretical concepts, you will also get experience with ANNs. You will work on a project where you will build an ANN to classify images. You will use the TensorFlow library to build your ANN, and you will see how to train your ANN on a dataset of images. By the end of this Project on Deep Learning - Artificial Neural Network course, you will have a deep understanding of ANNs and how to use them. You will be able to build your own ANNs to solve a variety of problems. You will also be able to use the TensorFlow library to build and train ANNs. So what are you waiting for? Enrol in this course today and start learning about the future of machine learning!   Learning Outcomes: Through this comprehensive course, you should be able to: Understand the fundamental concepts of deep learning and artificial neural networks. Install and configure an artificial neural network framework. Preprocess and structure data for optimal model performance. Encode data effectively for neural network training and predictions. Build and deploy artificial neural networks for real-world applications. Address data imbalance challenges and optimise model accuracy.   Who is this course for? This Project on Deep Learning - Artificial Neural Network course is ideal for: Data scientists and machine learning practitioners seeking to expand their knowledge. Software engineers interested in leveraging deep learning techniques. Students pursuing a career in artificial intelligence and machine learning. Professionals looking to enhance their skills in neural network development. Individuals with a passion for exploring advanced machine learning techniques.   Career Path  Our course will prepare you for a range of careers, including: Deep Learning Engineer: £40,000 - £100,000 per year. Machine Learning Researcher: £45,000 - £120,000 per year. Data Scientist: £50,000 - £110,000 per year. Artificial Intelligence Specialist: £55,000 - £130,000 per year. Software Engineer (specialising in AI): £45,000 - £100,000 per year. Research Scientist (Machine Learning): £50,000 - £120,000 per year. AI Consultant: £60,000 - £150,000 per year. Certification After studying the course materials of the Project on Deep Learning - Artificial Neural Network (ANNs) there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Prerequisites This Project on Deep Learning - Artificial Neural Network (ANNs) does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Project on Deep Learning - Artificial Neural Network (ANNs) was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection.   Course Curriculum Section 01: Introduction Introduction of Project 00:03:00 Section 02: ANN Installation Setup Environment for ANN 00:11:00 ANN Installation 00:09:00 Section 03: Data Preprocessing Import Libraries and Data Preprocessing 00:11:00 Data Preprocessing 00:07:00 Data Preprocessing Continue 00:10:00 Section 04: Data Encoding Data Exploration 00:10:00 Encoding 00:07:00 Encoding Continue 00:06:00 Preparation of Dataset for Training 00:04:00 Section 05: Steps to Build ANN Steps to Build ANN Part 1 00:06:00 Steps to Build ANN Part 2 00:06:00 Steps to Build ANN Part 3 00:06:00 Steps to Build ANN Part 4 00:09:00 Section 06: Predictions and Imbalance-Learn Predictions 00:11:00 Predictions Continue 00:08:00 Resampling Data with Imbalance-Learn 00:09:00 Resampling Data with Imbalance-Learn Continue 00:08:00

Mending garments extends their life. Learn how to properly sew buttons, restore stitching, fix hems, and employ undetectable repairing techniques. You'll also appreciate the social and artistic sides of mending with others, as well as lowering your carbon footprint by avoiding fast fashion. Book your place today and revamp your wardrobe with some basic but efficient clothing mending techniques!

Step into the intricate world of artificial neural networks with a course that sheds light on one of the most dynamic branches of deep learning. Designed for those keen to explore the structure, function and logic behind intelligent systems, this course blends academic insight with a clear, structured approach to the evolving digital frontier. From perceptrons to multilayer networks, it offers a layered understanding of how machines mimic the human brain’s decision-making process — minus the caffeine and existential crises. Whether you're sharpening your knowledge or stepping into the field with curiosity, this course provides a sharp focus on the core principles that power technologies like image recognition, voice synthesis and predictive modelling. Delivered in an accessible format, it caters to learners who want depth without the fluff, logic without the waffle, and progress without the guesswork. Neural networks may be artificial — but your understanding of them won’t be. Learning Outcomes: Gain a solid understanding of artificial neural networks and their applications in deep learning. Learn how to install the necessary packages and preprocess data for neural network training. Discover how to encode data and build your own artificial neural network using Python. Understand the steps involved in making predictions using your neural network model. Learn how to deal with imbalanced data in your neural network training. The Project on Deep Learning - Artificial Neural Network course is designed to provide you with the skills and knowledge you need to build your own neural network and perform complex tasks using deep learning. You'll learn how to install the necessary packages, preprocess data, and encode data for neural network training. You'll also gain a deeper understanding of artificial neural networks and learn how to build your own model using Python. By the end of the course, you'll be able to make predictions using your neural network model and understand how to deal with imbalanced data in your training. Project on Deep Learning - Artificial Neural Network Course Curriculum Section 01: Introduction Section 02: ANN Installation Section 03: Data Preprocessing Section 04: Data Encoding Section 05: Steps to Build ANN Section 06: Predictions and Imbalance-Learn How is the course assessed? Upon completing an online module, you will immediately be given access to a specifically crafted MCQ test. For each test, the pass mark will be set to 60%. Exam & Retakes: It is to inform our learners that the initial exam for this online course is provided at no additional cost. In the event of needing a retake, a nominal fee of £9.99 will be applicable. Certification Upon successful completion of the assessment procedure, learners can obtain their certification by placing an order and remitting a fee of __ GBP. £9 for PDF Certificate and £15 for the Hardcopy Certificate within the UK ( An additional £10 postal charge will be applicable for international delivery). CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Data analysts who want to expand their skills in deep learning and artificial neural networks. Programmers who want to learn how to build their own neural network models for advanced tasks. Entrepreneurs who want to develop their own deep learning-based applications. Students who want to enhance their skills in deep learning and prepare for a career in the field. Anyone who wants to explore the world of artificial neural networks and deep learning projects. Career path Data Analyst: £24,000 - £45,000 Machine Learning Engineer: £28,000 - £65,000 Deep Learning Engineer: £30,000 - £75,000 Technical Lead: £40,000 - £90,000 Chief Technology Officer: £90,000 - £250,000 Certificates Certificate of completion Digital certificate - £9 You can apply for a CPD Accredited PDF Certificate at the cost of £9. Certificate of completion Hard copy certificate - £15 Hard copy can be sent to you via post at the expense of £15.

A two-day, beginner, hands-on course to rebuild a section of dry-stone wall, learning the age old techniques of this satisfying craft