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AI Capstone Project with Deep Learning

AI Capstone Project with Deep Learning

About this course.

In this capstone, learners will apply their deep learning knowledge and expertise to a real world challenge. They will use a library of their choice to develop and test a deep learning model. They will load and pre-process data for a real problem, build the model and validate it. Learners will then present a project report to demonstrate the validity of their model and their proficiency in the field of Deep Learning. Learning Outcomes: • determine what kind of deep learning method to use in which situation • know how to build a deep learning model to solve a real problem • master the process of creating a deep learning pipeline • apply knowledge of deep learning to improve models using real data • demonstrate ability to present and communicate outcomes of deep learning projects

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College of Computing

Students pres

SCI Pilots AI-Enhanced Capstone to Advance Software Engineering Instruction

Friday, May 10, 2024

Emily Smith

College of computing school of computing instruction.

Artificial Intelligence (AI) is transforming industries and redefining problem-solving methods, especially within the rapidly evolving tech sector. 

A recent Forbes article highlights a significant shift in recruitment strategies, noting an increasing demand for professionals who can effectively leverage AI alongside their technical skills. 

"The demand for skilled professionals who can adeptly use AI has never been higher," the article states, emphasizing the need for complex problem-solving abilities and technical proficiency.

The School of Computing Instruction (SCI) at Georgia Tech is responding to these industry shifts by launching a transformative initiative this summer. The redesigned Computer Science (CS) capstone course bridges the gap between academic learning and real-world software development demands. 

"Students still need a foundational understanding of computer science because these tools aren’t perfect, but we want to equip them with the ability to use them," SCI Chair Olufisayo Omojokun said. 

"With this redesign, we're positioning the capstone as a platform for testing and refining the application of generative AI technologies in real-world scenarios."

SCI Chair Olufisayo Omojokun judges student projects at the Capstone expo. Photos by Terence Rushin/ College of Computing.

Course Overview

Led by SCI Lecturer Nimisha Roy, the course is designed to simulate the tight deadlines of the industry, offering students practical experience of project constraints. This summer, students will choose from various projects centered around developing Google Chrome apps, with each project designed to challenge and enhance their skills in software design, implementation, testing, and project management.

"The course starts by grounding students in traditional software development methods to establish a solid base," Roy said. "Students first create system design artifacts using conventional approaches. They then enhance these designs using AI-driven tools like Lucidchart and Mermaid, allowing for a direct comparison between traditional and AI-enhanced processes.”

She says this approach not only highlights the transformative impact of AI on design productivity and quality but also emphasizes the crucial role of documentation in software development.

SCI's Nimisha Roy works with students at the Spring 2024 Capstone Expo. Photos by Terence Rushin.

AI tools like GitHub Copilot, Codeium, and Testim are introduced to streamline coding and testing processes for the implementation phase. 

"We anticipate that the integration of AI from the beginning of the implementation phase will significantly boost productivity and enable the development of more complex features compared to traditional methods," Roy said. 

Students will rigorously test this hypothesis by comparing the quality of design documentation and final software products against those from previous semesters.

Objectives and Impact

Reflecting on the course's goals, Roy said, "This isn't just about enhancing technical skills. It's about preparing students to critically assess the role of AI in software development, considering its impact on productivity, output quality, user engagement, and the learning curve associated with adaptability."

She adds that this initiative underscores Georgia Tech's dedication to pioneering advancements in CS education that bridge the gap between academic learning and industry demands, setting a new standard for educational practices.

Students present their software design projects at the Spring 2024 Capstone Expo. Over the summer, students will use AI tools during the program. Photos by Terence Rushin/ College of Computing.

Future Directions

As the course unfolds, there is a palpable sense of excitement and anticipation regarding its potential future impact. Beyond the immediate objectives, future iterations of the capstone course may explore further advancements in AI technologies and their implications for software development practices.

“Using these tools could potentially lead to a scenario where future capstone projects involve students accomplishing more or higher-quality projects,” said Omojokun.

SCI’s initiative marks a significant shift in how future software developers are trained and sets a new standard in educational practices, aligning closely with industry advancements and future needs.

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InterviewBit

Top 20 Artificial Intelligence Projects With Source Code [2023]

Introduction, artificial intelligence projects for beginners, 1. product recommendation systems, 2. plagiarism analyzer, 3. prediction of bird species, 4. dog and cat classification, 5. next word prediction, intermediate artificial intelligence projects, 6. face recognition, 7. mask detection, 8. heart disease prediction, 9. cv analysis, 10. sales predictor, 11. automated attendance system, 12. pneumonia detection, advanced artificial intelligence projects, 13. ai chatbots, 14. ai self-driving cars, 15. image colorization, 16. game of chess, 17. human pose estimation, 18. face aging, 19. image caption generator, 20. voice-based virtual assistant, q.1: how do i start my own ai project, q.2: is google an ai, q.4: can i create my own ai, q.5: can i learn ai without coding, additional resources.

If you think back 30 years, humans could never have dreamed that artificial intelligence would take such a big step forward and have such a positive impact on our lives. Artificial Intelligence has accelerated life’s pace. Artificial intelligence (AI) has given rise to applications that are now having a significant impact on our lives.

The term AI was initially coined in 1956 at a Dartmouth meeting. Artificial intelligence (AI) is the ability of a computer or a computer-controlled robot to accomplish tasks that would normally be performed by intelligent beings. In today’s world, Artificial Intelligence has become highly popular. It is the simulation of human intelligence in computers that have been programmed to learn and mimic human actions. These machines can learn from their mistakes and execute activities that are similar to those performed by humans.

Building an AI system is a painstaking process of reversing our features and talents in a machine and then leveraging its computing strength to outperform our abilities. To comprehend how Artificial Intelligence works, one must go deeply into the many sub-domains of AI and comprehend how those domains can be applied to various industries of the industry. Machine learning, deep learning, neural networks, computer vision, and natural language processing are examples of these fields.

Confused about your next job?

Artificial Intelligence entities are constructed for a variety of goals, which is why they differ. The following are the several types of artificial intelligence:

  • Artificial Narrow Intelligence (ANI)
  • Artificial General Intelligence (AGI)
  • Artificial Super Intelligence (ASI)

Artificial Intelligence’s goal is to augment human capabilities and assist us in making complex decisions with far-reaching repercussions. AI performs regular, high-volume, automated tasks rather than automating manual ones. And it does so consistently and without tiring. Humans still need to set up the system and ask the correct questions, of course.

AI adapts by allowing data to program itself using progressive learning algorithms. In order for algorithms to learn, AI looks for structure and regularities in data. An algorithm can train itself to play chess, just as it can educate itself to recommend a product. Deep neural networks are used by AI to attain remarkable precision. Your interactions with Alexa and Google, for example, are all based on deep learning. And the more you use these things, the more accurate they become. Deep learning and object identification AI techniques can now be utilized in the medical profession to spot cancer on medical photos with greater accuracy.

In this blog, you will come across various such applications of artificial intelligence that can be opted as a project idea for your college assignments or personal development. Let’s dive into this.

Below are a few exciting AI Projects to try. We have divided projects based on beginner, intermediate, and advanced levels.

Recommender systems have become more prevalent in our lives as a result of the emergence of Youtube, Amazon, Netflix, and other similar web services. They’re algorithms that help people find items that are relevant to them. In some businesses, recommender systems are crucial since they can produce a large amount of revenue or serve as a method to differentiate yourself from competitors. It determines the compatibility of the user and the object, as well as the similarities between users and items, in order to make recommendations.

Source Code: Product Recommendation System

On the internet, plagiarism is widespread. The internet is brimming with content, which can be found on millions of different websites. It can be tough to tell which content is plagiarised and which is not at times. Authors of blog postings should check to see if their work has been stolen and put elsewhere. News organizations should investigate whether a content farm has stolen their news pieces and claimed them as their own. The task is demanding. What if you had your own plagiarism detection software? This opportunity is provided by AI.

Source Code: Plagiarism Analyzer

Manual classification of birds can be done by topic experts, but it has become a hard and time-consuming process due to the vast accumulation of data. Artificial intelligence-based categorization becomes critical in this situation. This classification-based AI project can be approached in two ways. If you’re a newbie, you can use a random forest to forecast bird species. To get to an intermediate level, you can utilize a convolution neural network.

Source Code: Bird Species Prediction

Dogs vs. Cats is a simple computer vision project concept that entails categorizing photographs into one of two categories. There were various machine learning algorithms used to handle this use case, however, deep learning convolutional neural networks were the most effective in the recent several years. It can be used to learn and practice building, evaluating, and using convolutional deep-learning neural networks for image categorization from the ground up. You will gain a thorough understanding of how to apply CNN in advanced AI projects as a result of doing so.

Source Code: Dog and Cat Classification

It’s never easy to write rapidly and without making spelling mistakes. It is not difficult to type correctly and quickly while using a keyboard on a desktop computer, but typing on small devices such as mobile phones is a different story, and it can be frustrating for many of us. With the next word prediction project, you can improve your experience of typing on small devices only by predicting the next word in a sentence fragment. You won’t have to type complete sentences because the algorithms will predict the next word for you, and typos will be much reduced.

Source Code: Next Word Prediction

Facial recognition is a technique for recognizing or verifying a person’s identification by looking at their face. This technology can recognize persons in photographs, videos, and in real-time. A type of biometric security is facial recognition. Although there is growing interest in other applications, the technology is mostly employed for security and law enforcement. Typically, face recognition does not need a large database of images to identify an individual’s identification; rather, it merely identifies and recognizes one person as the device’s only owner, while restricting access to others.

Source Code: Face R e cognition

Face mask detection is the process of determining whether or not someone is wearing a mask. We all know that wearing masks is one of the most effective ways to prevent the virus from spreading. Despite this, we notice a lot of people not wearing masks in public locations. Using AI approaches to construct a system that can recognize persons who aren’t wearing masks could be a solution to this problem.

Source Code: Mask Detection

From a medical standpoint, this project is advantageous because it is designed to provide online medical advice and guidance to individuals suffering from cardiac disorders. The application will be taught and fed information about a variety of various cardiac diseases. This clever system uses artificial intelligence (AI) approaches to predict the most accurate disease that might be linked to the information provided by a patient. Users can then seek medical advice from specialists based on the system’s diagnosis.

Source Code: Heart Disease Prediction

One of the more intriguing Artificial Intelligence project concepts is this. Shortlisting deserving individuals from a large pile of CVs is a difficult undertaking. The goal of this project is to develop cutting-edge software that can give a legally sound and equitable CV ranking system. Candidates will be ranked for a specific job profile based on their abilities and expertise. It will also take into account all other important factors, such as soft skills, interests, professional qualifications, and so on. This will exclude all unsuitable candidates for a job role and produce a list of the best contenders for the position.

Source Code: CV Analysis

Any business has an abundance of products, but how they manage to keep track of each product’s sales is beyond our comprehension. That’s where a sales forecaster can help. It allows you to keep track of new product arrivals and out-of-stock items. Sales Predictor is going to be a huge undertaking. You must devise an algorithm to determine how many products are sold on a daily basis and forecast sales for that product on a weekly or monthly basis.

Source Code: Sales Predictor

An automatic attendance system is one that keeps track of individuals’ attendance at a school. Unlike a traditional attendance system, automatic attendance software allows staff to record, store, and monitor students’ attendance history while also efficiently managing the classroom. It does not include the usage of paper or human effort. The technology is beneficial since it generates a detailed report on each class’ attendance. It saves time, money, and institutes resources for the user.

Source Code: Automated Attendance System

Pneumonia is typically identified by doctors using chest X-rays. However, AI is capable of identifying disease in X-ray images of patients. Convolution Neural Networks (CNNs) are used to develop the AI system. By analysing chest X-ray scans, the AI project can automatically determine whether a patient has pneumonia or not. Because people’s lives are on the line, the algorithm has to be highly precise.

Source Code: Pneumonia Detection

Creating a chatbot is one of the top AI-based initiatives. You should begin by developing a basic customer service chatbot. You can get ideas from chatbots that can be found on numerous websites. After you’ve constructed a basic chatbot, you can refine it and create a more complex version. Artificial intelligence enables you to fly and supports you in putting your ideas into reality.

Source Code: AI Chatbot

Artificial intelligence algorithms enable self-driving cars. They allow an automobile to collect data about its surroundings from cameras and other sensors, analyze it, and decide what actions to take. Artificial intelligence breakthroughs have allowed cars to learn to perform these tasks better than humans. It made use of complex math and image recognition techniques. This project is open to those who are AI enthusiasts in college or who have recently graduated from college.

Source Code: AI Self Driving Car

Many of us have a difficult time picturing the colors that the moment captured would have contained when looking at vintage grayscale pictures. To alleviate human suffering, artificial intelligence provides the ideal solution, since it can be used to create a smart image colorization system. The technique of adding colors to a grayscale image in order to make it more visually pleasing and perceptually significant is known as image colorization.

Source Code: Image Colorization

Chess is a popular game, and in order to improve our enjoyment of it, we need to implement a good artificial intelligence system that can compete with humans and make chess a difficult task. Artificial intelligence has changed how top-level chess games are played. The majority of Grandmasters and Super Grandmasters use these latest Artificial Intelligence chess engines to evaluate their own and their opponents’ games.

Source Code: Game of Chess

The art of determining a person’s body alignment by calculating various body joints is known as human pose estimate. It’s a computer vision technique for tracking a person’s or an object’s movements. This is normally accomplished by locating critical spots for the things in question. Snapchat employs position estimation to figure out where the person’s eyes and head are in order to apply a filter. Similarly, we can estimate a human stance in real time and apply filters to the person.

Source Code: Human Pose Estimation

Generative Adversarial Networks (GANs) are a sort of deep neural network design that generates data through unsupervised machine learning. We can now produce high-resolution picture alterations thanks to the recent success of GAN architectures. You may make an application that takes an image of a human as input and returns a picture of that same person in 30 years. It’s a little tricky to put GANs in place.

Source Code: Face Aging

Caption generation is a difficult artificial intelligence challenge in which a textual description for a given photograph must be created. It necessitates both computer vision technologies for comprehending the image’s content and a natural language processing language model for converting the image’s comprehension into words in the correct order. Deep learning approaches have recently reached state-of-the-art results.

Source Code: Image Caption Generator

One of the more intriguing Artificial Intelligence project concepts is this. Voice-activated personal assistants are useful tools for making routine activities easier. You may use virtual voice assistants to do things like search the web for items/services, shop for products for you, compose notes and create reminders, and so much more. Because the assistant has been taught to understand normal human language, it will recognize the command and save it in the database. It will deduce a user’s purpose from the spoken phrase and take appropriate action. It can also convert text to speech.

Source Code: Voice-based Virtual Assistant

Some of the popular Tools and Frameworks that can be used for an AI project are:

  • Scikit Learn

Some of the popular languages that can be used to create your AI projects are:

  • Python (most popular)

We’ve discussed 20 AI project ideas in this article. We began with some simple projects that you can complete quickly. After you’ve completed these beginner tasks, I recommend going back to understand a few additional principles before moving on to the intermediate projects. After you’ve gained confidence, you can go on to the intermediate tasks. This will boost morale in moving on to more sophisticated tasks. You should get your hands on these Artificial Intelligence project ideas if you want to boost your AI skills. These tasks will assist you in honing your AI skills. Furthermore, these projects will not only put you on the route to becoming an AI specialist, but they will also prepare you for the workforce. This will also improve your chances of getting hired. So don’t stop learning.

Ans: Following are some typical steps to get started with an AI project:

  • Pick a topic you are interested in. That can be any problem statement.
  • Learn some concepts of AI.
  • Find a quick solution to the problem statement chosen.
  • Improve your simple solution to make it more optimized.
  • Share your solution.
  • Repeat the process of improvement.
  • Pick up the efficient AI algorithm(s) that could solve your problem.
  • Analyze your results.
  • Improve your algorithm using AI techniques.

Ans: Google is a company that makes use of Artificial Intelligence to build extraordinary products like Google Photos, Gmail, Self-driving cars, recommendation systems, etc. You can learn more about it at this link .

Ans: Yes, it is possible to build your own AI. You can gain the required skills by practising more on the AI concepts and working on projects from beginner to advanced level. 

Ans: Yes, at some level it is possible to learn AI without coding. There are various tools available that can be helpful in doing such learning. But if you are aiming to be a part of the IT industry, it is recommended to learn to code as well. You can also check out Scaler Topics’ Free Deep Learning course to get started in AI.

  • Artificial Intelligence Interview Questions
  • Artificial Intelligence MCQ
  • Applications of Artificial Intelligence
  • Artificial Intelligence Books
  • Characteristics of Artificial Intelligence
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  • Difference Between Artificial Intelligence and Machine Learning
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Top 27 Generative AI Projects Ideas with Source Codes

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Generative AI Projects: Do you want to explore and discover breakthroughs in the world of generative AI? With projects as diverse as artificial music composition, image generation and text synthesis

Generative AI Projects

This emerging technology has allowed for developers to create impressive models that can generate new content or ideas based on existing patterns. 

Generative AI is rapidly gaining traction and becoming an important tool not just in the tech space but also other industries such as healthcare, retail, finance, education and more. If you’re looking to get your feet wet with generative AI or simply curious about what projects are out there then look no further! This blog post will outline some top project ideas so that you can dive deep into this exciting new technology.

A great place to start is with Master Generative AI: Data Science Course by Physics Wallah – it gives a comprehensive overview of the technology alongside step-by-step project tutorials and resources. To save some money while learning, utilize coupon code “ READER ” when enrolling in the course to enjoy a discount off your purchase!

Table of Contents

Generative AI Projects for Beginners

Below table shows the generative AI projects for beginners :

Also read:  What is Generative AI? Everything You Need to Know in 2024

Generative AI Projects with Source Code

Below are some generative AI projects with source code you can try:

1) Build a Data Science Portfolio Website with ChatGPT:

  • Description: Create a website showcasing your data science projects and skills. Integrate ChatGPT to provide an interactive element, allowing visitors to ask questions or receive information about your projects.
  • Key Components: HTML, CSS, JavaScript for website development; ChatGPT API for interactive chat features.
  • Source code:  https://medium.com/towards-data-science/how-to-build-a-data-science-portfolio-website-with-chatgpt-e57d29badf7f

2) Personalized Voice Assistant with GPT and Whisper:

  • Description: Develop a voice assistant using GPT (Generative Pre-trained Transformer) for natural language understanding and Whisper for realistic text-to-speech synthesis. This project aims to create a personalized and conversational AI voice assistant.
  • Key Components: GPT for natural language processing; Whisper for text-to-speech synthesis; Python for integration.
  • Source code: https://github.com/reese3222/nanoassistant

3) Build your AI translator:

  • Description: Construct an AI-powered language translator that can translate text from one language to another. Utilize pre-trained language models to handle translation tasks effectively.
  • Key Components: Natural Language Processing (NLP) libraries (e.g., spaCy), language translation APIs, Python for scripting.
  • Source code: https://artificialcorner.com/stop-using-google-translator-build-your-own-ai-application-ea8d3a896ff2

4) Summarize papers:

  • Description: Develop an application that automatically generates summaries for research papers or articles. Use natural language processing techniques to extract essential information and provide concise summaries.
  • Key Components: Natural Language Processing libraries (e.g., NLTK, spaCy), extractive or abstractive summarization techniques, Python.
  • Source code: https://medium.com/mlearning-ai/building-a-custom-summarization-app-with-streamlit-and-langchain-11ab19099822

5) Creating Code Documentation using Python:

  • Description: Build a tool that automates documentation generation for code projects. Extract comments, function descriptions, and other relevant information from the codebase to create comprehensive documentation.
  • Key Components: Python scripting, regular expressions for parsing code, documentation generation tools (e.g., Sphinx).
  • Source code: https://medium.com/@madhok.simran8/how-to-generate-python-docstring-with-chatgpt-openapi-ed055f302d31

6) Automate PowerPoint presentations:

  • Description: Create a system that automates the creation of PowerPoint presentations. This could involve generating slides based on data, incorporating visualizations, and dynamically updating content.
  • Key Components: Python for automation, libraries for data visualization (e.g., Matplotlib, Plotly), PowerPoint automation libraries.
  • Source code: https://www.youtube.com/watch?v=zogvDn5Kd8E&ab_channel=MatrixInception

Also read:  20+ Generative AI Examples in 2024 That Show AI’s Potential!

Generative AI Projects using Python

Here are the generative AI projects using Python. These project ideas aim to showcase the versatility of generative AI in creating unique and interactive experiences across various domains.

Also read:  Artificial Intelligence Course Syllabus 2024

Generative AI Projects Ideas

Below table shows the generative AI projects ideas you must try:

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Generative AI Projects for Final Year

For final-year projects, consider engaging in more advanced and comprehensive generative AI projects that demonstrate your proficiency in the field. Here are some project ideas:

1) Generative Adversarial Networks (GANs) for Image-to-Image Translation:

Implement GANs to translate images from one domain to another. For example, convert satellite images to maps or black-and-white photos to color. This project involves training a GAN to learn the mapping between two domains and generate realistic images.

2) Deep Reinforcement Learning for Game Generation:

Explore deep reinforcement learning to create a system that generates new levels or scenarios for video games. Train an agent to play the game and use its experiences to develop novel and challenging game environments.

3) Interactive Story Generation with Reinforcement Learning:

Develop an interactive storytelling system using reinforcement learning. Users can guide the story’s direction, and the model adapts its narrative generation based on user interactions, creating a dynamic and personalized storytelling experience.

Mastering Generative AI is a complex process, but it’s also worth the effort. By taking a data science course these projects become much more manageable, helping open up new fascinating possibilities. Thanks to all of the amazing project ideas out there, with source codes available, you can get started creating your own generative projects as soon as today! 

With so many great projects to choose from and ways to experiment with different tools and techniques, you’ll be able to develop your own tailored generative AI projects in no time. We highly recommend Physics Wallah’s ‘Master Generative AI: Data Science Course ‘ for those wanting to delve into the world of Generative Artificial Intelligence with real-world examples and plenty of practical exercises that’ll help you perfect your technique.

Also read:  15 Best Generative AI Tools To Check Out In 2024!

For Latest Tech Related Information, Join Our Official Free Telegram Group : PW Skills Telegram Group

What are some popular types of Generative AI projects?

Popular types include image synthesis, text generation, music composition, code generation, and various creative applications like art and design projects.

How can I get started with a Generative AI project?

Start by understanding Generative AI concepts and choose a specific domain or type of content you want to generate. Explore frameworks and models relevant to your preferred domain.

What programming languages are commonly used for Generative AI projects?

Python is widely used for Generative AI projects. Frameworks like TensorFlow and PyTorch, along with libraries like OpenCV and NLTK, are commonly employed.

Are there pre-trained models available for Generative AI projects?

Yes, many pre-trained models are available, such as GPT for text generation, DALL-E for image synthesis, and various models for music generation. These can be fine-tuned for specific project needs.

Can Generative AI be used for practical applications beyond creative projects?

Absolutely. Generative AI has practical applications in areas like medical image generation, code completion, language translation, and even in simulations for training autonomous systems.

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  1. GitHub

    1 . This Repository contains the 4 week AI Capstone project assignment using keras as a part of IBM-AI Engineering in which we need to classify a image containing a stone cracked or not by processing 40000 images in which nearly 30000 for training and 10000 for validation.

  2. Coursera AI Capstone Project with Deep Learning

    AI Capstone Project with Deep Learning. These are the notebooks from my coursework for IBM's AI Capstone Project with Deep Learning on Coursera. I took the Keras track for this course, which involved training and testing a deep learning model to identify cracks in images of concrete. This course introduced me to the concept of leveraging pre ...

  3. capstone-project · GitHub Topics · GitHub

    To associate your repository with the capstone-project topic, visit your repo's landing page and select "manage topics." GitHub is where people build software. More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects.

  4. Kabuin/IBM-AI-Capstone-Project-with-deep-learning

    The particular pre-trained model will be resnet18; you will have three questions - Kabuin/IBM-AI-Capstone-Project-with-deep-learning In this lab, you will use pre-trained models to classify between the negative and positive samples; you will be provided with the dataset object.

  5. AI-Capstone-Project-with-Deep-Learning/_AI-Capstone-Project ...

    {"payload":{"allShortcutsEnabled":false,"fileTree":{"":{"items":[{"name":"1_0_load_and_display_data.ipynb","path":"1_0_load_and_display_data.ipynb","contentType ...

  6. capstone-project · GitHub Topics · GitHub

    This repository is used to track issues and pull requests for our CS Capstone for Spring '23. We are developing control software for a robotic prototype that will be used in a research lab for further research into infant feeding issues and potential solutions. qt cpp arduino-nano capstone-project. Updated 3 days ago.

  7. Applied AI with DeepLearning Course by IBM

    AI Capstone Project with Deep Learning. This course is part of IBM AI Engineering Professional Certificate. Taught in English. 22 languages available. Some content may not be translated. Instructors: Alex Aklson. +1 more. Enroll for Free. Starts May 12.

  8. AI Capstone Project with Deep Learning

    In this capstone, learners will apply their deep learning knowledge and expertise to a real world challenge. They will use a library of their choice to develop and test a deep learning model. They will load and pre-process data for a real problem, build the model and validate it.

  9. Badge: AI Capstone Project with Deep Learning

    This earner has deep learning knowledge and expertise to develop and test a deep learning model and is proficient in the field of Deep Learning. They are able to determine what kind of deep learning method to use in situations, and know how to build a deep learning model to solve a real problem. They have mastered the process of creating a deep ...

  10. AI Capstone Project with Deep Learning

    In this capstone, learners will apply their deep learning knowledge and expertise to a real world challenge. They will use a library of their choice to develop and test a deep learning model. They ...

  11. AI Series: AI in Healthcare Capstone Project

    Stanford Center for Continuing Medical Education, AI Series: AI in Healthcare Capstone Project, 11/16/2020 12:00:00 AM - 11/15/2023 11:59:00 PM, Internet Enduring Material Sponsored by Stanford University School of Medicine. Presented by the Center for Health Education at Stanford University School of Medicine. This capstone project course takes the learner on a guided tour exploring all the ...

  12. Applied AI with DeepLearning Course by IBM

    There are 5 modules in this course. This capstone project takes you on a guided tour exploring all the concepts we have covered in the different classes up till now. We have organized this experience around the journey of a patient who develops some respiratory symptoms and given the concerns around COVID19 seeks care with a primary care provider.

  13. ai-capstone-project · GitHub Topics · GitHub

    The ai-capstone-project topic hasn't been used on any public repositories, yet. ai-capstone-project. ai-capstone-project. GitHub is where people build software. More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects.

  14. 10 GitHub Repositories to Master Machine Learning

    Over the course, participants will gain practical experience in areas like deep learning, serverless model deployment, and ensemble techniques. The curriculum culminates in two capstone projects that enable students to demonstrate their newly-developed skills. 6. Machine Learning Tutorials . Repository: ujjwalkarn/Machine-Learning-Tutorials

  15. AI Capstone Project with Deep Learning · GitHub

    Created 4 years ago. Star 0. Fork 0. AI Capstone Project with Deep Learning. Raw. Lab - Loading and Viewing Data.ipynb. AI Capstone Project with Deep Learning. GitHub Gist: instantly share code, notes, and snippets.

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    It is a AI Capstone project done as a part of IBM AI Engineering - GitHub - ksdkamesh99/AI-Capstone-Project: It is a AI Capstone project done as a part of IBM AI ...

  17. SCI Pilots AI-Enhanced Capstone to Advance Software Engineering

    Artificial Intelligence (AI) is transforming industries and redefining problem-solving methods, especially within the rapidly evolving tech sector. ... SCI Chair Olufisayo Omojokun judges student projects at the Capstone expo. Photos by Terence Rushin/ College of Computing. ... AI tools like GitHub Copilot, Codeium, and Testim are introduced to ...

  18. Starbucks Capstone Project

    Starbucks Capstone Project. Towards AI Team. 54 likes. June 13, 2020. ... To see a more detailed analysis with numbers and codes, check the project's Github repository. ... Towards AI is the world's leading artificial intelligence (AI) and technology publication. Read by thought-leaders and decision-makers around the world.

  19. Artificial Intelligence in Healthcare Capstone

    In the capstone project, you will take a guided, interactive tour through the patient journey to see how different decisions can create different datasets and outcomes, and how regulatory and ethical limitations affect its process. With hands-on experience in the position of a medical data miner, you'll see how data has the power to transform ...

  20. Top 20 Artificial Intelligence Projects With Source Code [2024]

    Source Code: Image Colorization. 16. Game of Chess. Chess is a popular game, and in order to improve our enjoyment of it, we need to implement a good artificial intelligence system that can compete with humans and make chess a difficult task. Artificial intelligence has changed how top-level chess games are played.

  21. Top 27 Generative AI Projects Ideas With Source Codes

    Build an AI curator for virtual art galleries, generating curated exhibitions based on themes, art styles, or historical periods, offering users a unique exploration of virtual art spaces. 6. AI-Enhanced Escape Room Generator. Generate puzzles, clues, and challenges dynamically for an escape room experience.

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    AI Capstone projectwith Pytorch - Classifying Concrete cracks. Steps: Loading and displaying data. Data Preparation. Build Linear Classifier with Pytorch. Use pre-trained models with Resnet-18.

  23. Responsible AI

    Course Communications. Please send any questions to the Responsible AI Discord server: Discord server: 5RFCXBfK3f. Primary Course Contact, email Emily Ramond ([email protected]) Replication Project contact, email Parker Addison ([email protected]) For private or personal questions, you can reach out to Emily privately via email or Discord.