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I strongly believe that to get a job in the field of artificial intelligence, you need to have a strong portfolio. This means that you need to show recruiters that you can create ai models and applications that solve real-world problems.
In this blog, we will discuss seven ai portfolio projects that will enhance your resume. These projects include tutorials, source code, and other supporting materials to help you build suitable ai applications.
1. Build and deploy your machine learning application in 5 minutes
Project link: Create an ai chatbot in 5 minutes with Hugging Face and Gradio
<img decoding="async" alt="7 ai portfolio projects to boost your resume” width=”100%” src=”https://technicalterrence.com/wp-content/uploads/2024/08/1722881310_472_7-AI-portfolio-projects-to-boost-your-resume.png”/><img decoding="async" src="https://technicalterrence.com/wp-content/uploads/2024/08/1722881310_472_7-AI-portfolio-projects-to-boost-your-resume.png" alt="7 ai portfolio projects to boost your resume” width=”100%”/>
Screenshot of the project
In this project, you will build a chatbot application and deploy it to Hugging Face spaces. It is a beginner-friendly ai project that requires minimal knowledge of language models and Python. First, you will learn several components of the Gradio Python library to build a chatbot application and then use the Hugging Face ecosystem to upload the model and deploy it.
It's that easy.
2. Build ai projects with DuckDB – SQL query engine
Project link: ai-projects-with-duckdb” rel=”noopener” target=”_blank”>DuckDB Tutorial: Building ai Projects
<img decoding="async" alt="7 ai portfolio projects to boost your resume” width=”100%” src=”https://technicalterrence.com/wp-content/uploads/2024/08/1722881310_333_7-AI-portfolio-projects-to-boost-your-resume.png”/><img decoding="async" src="https://technicalterrence.com/wp-content/uploads/2024/08/1722881310_333_7-AI-portfolio-projects-to-boost-your-resume.png" alt="7 ai portfolio projects to boost your resume” width=”100%”/>
Screenshot of the project
In this project, you will learn how to use DuckDB as a vector database for a RAG application and also as a SQL query engine using the LlamaIndex framework. The query will take a natural language input, convert it to SQL, and output the result in natural language. It is a simple and straightforward project for beginners, but before you dive into building the ai application, you should learn some basics of DuckDB’s Python API and the LlamaIndex framework.
3. Building a multi-step ai agent using LangChain API and Cohere
Project link: Cohere Command R+: A Complete Step-by-Step Tutorial
<img decoding="async" alt="7 ai portfolio projects to boost your resume” width=”100%” src=”https://technicalterrence.com/wp-content/uploads/2024/08/1722881311_541_7-AI-portfolio-projects-to-boost-your-resume.png”/><img decoding="async" src="https://technicalterrence.com/wp-content/uploads/2024/08/1722881311_541_7-AI-portfolio-projects-to-boost-your-resume.png" alt="7 ai portfolio projects to boost your resume” width=”100%”/>
Screenshot of the project
Cohere API is better than OpenAI API in terms of functionality for developing ai applications. In this project, we will explore the various features of Cohere API and learn how to build a multi-step ai agent using the LangChain ecosystem and the Command R+ model. This ai application will take the user’s query, search the web using the Tavily API, generate Python code, execute the code using the Python REPL, and then return the visualization requested by the user. This is an intermediate-level project for people with basic knowledge and interested in building advanced ai applications using the LangChain framework.
4. Flame 3 fine tuning and local use
Project link: How to perfect Llama 3 and use it locally: a step-by-step guide | DataCamp
<img decoding="async" alt="7 ai portfolio projects to boost your resume” width=”100%” src=”https://technicalterrence.com/wp-content/uploads/2024/08/1722881311_836_7-AI-portfolio-projects-to-boost-your-resume.png”/><img decoding="async" src="https://technicalterrence.com/wp-content/uploads/2024/08/1722881311_836_7-AI-portfolio-projects-to-boost-your-resume.png" alt="7 ai portfolio projects to boost your resume” width=”100%”/>
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A popular project on DataCamp that will help you fine-tune any model using free resources and convert the model to Llama.cpp format so that it can be used locally on your laptop without internet. First you will learn how to fine-tune the Llama-3 model on a medical dataset, then you will merge the adapter with the base model and submit the completed model to Hugging Face Hub. After that, you will convert the model files to GGUF Llama.cpp format, quantize the GGUF model and submit the file to Hugging Face Hub. Finally, you will use the fine-tuned model locally with the Jan app.
5. Multilingual automatic speech recognition
Model repository: kingabzpro/wav2vec2-large-xls-r-300m-Urdu
Code repository: kingabzpro/Urdu-ASR-SOTA
Tutorial link: Fine-tuning XLSR-Wav2Vec2 for low-end ASR with Transformers
<img decoding="async" alt="7 ai portfolio projects to boost your resume” width=”100%” src=”https://technicalterrence.com/wp-content/uploads/2024/08/1722881310_333_7-AI-portfolio-projects-to-boost-your-resume.png”/><img decoding="async" src="https://technicalterrence.com/wp-content/uploads/2024/08/1722881310_333_7-AI-portfolio-projects-to-boost-your-resume.png" alt="7 ai portfolio projects to boost your resume” width=”100%”/>
Screenshot of kingabzpro/wav2vec2-large-xls-r-300m-Urdu
My most popular project! It gets almost half a million downloads every month. I fine-tuned the Wave2Vec2 Large model on an Urdu dataset using the Transformer library. After that, I improved the results of the generated output by integrating the language model.
<img decoding="async" alt="7 ai portfolio projects to boost your resume” width=”100%” src=”https://technicalterrence.com/wp-content/uploads/2024/08/1722881311_952_7-AI-portfolio-projects-to-boost-your-resume.png”/><img decoding="async" src="https://technicalterrence.com/wp-content/uploads/2024/08/1722881311_952_7-AI-portfolio-projects-to-boost-your-resume.png" alt="7 ai portfolio projects to boost your resume” width=”100%”/>
Screenshot of Urdu ASR SOTA – A Face Hugging Space by kingabzpro
In this project, you will fine-tune a speech recognition model in your preferred language and integrate it with a language model to improve its performance. Then, you will use Gradio to build an ai application and deploy it to the Hugging Face server. Fine-tuning is a challenging task that requires learning the basics, cleaning the audio and text dataset, and optimizing the model training.
6. Building CI/CD Workflows for Machine Learning Operations
Project link: Beginner's Guide to CI/CD for Machine Learning | DataCamp
<img decoding="async" alt="7 ai portfolio projects to boost your resume” width=”70%” src=”https://technicalterrence.com/wp-content/uploads/2024/08/1722881311_532_7-AI-portfolio-projects-to-boost-your-resume.png”/><img decoding="async" src="https://technicalterrence.com/wp-content/uploads/2024/08/1722881311_532_7-AI-portfolio-projects-to-boost-your-resume.png" alt="7 ai portfolio projects to boost your resume” width=”70%”/>
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Another popular project on GitHub. It involves building a CI/CD pipeline or machine learning operations. In this project, you will learn about machine learning project templates and how to automate the processes of training, evaluating, and deploying models. You will learn about MakeFile, GitHub Actions, Gradio, Hugging Face, GitHub Secrets, CML actions, and various Git operations.
Ultimately, you will build end-to-end machine learning pipelines that will run when new data is fed or code is updated. You will use new data to retrain the model, generate model evaluations, extract the trained model, and deploy it to the server. It is a fully automated system that generates logs at every step.
7. Fine-tuning Stable Diffusion XL with DreamBooth and LoRA
Project link: Fine-tuning Stable Diffusion XL with DreamBooth and LoRA | DataCamp
<img decoding="async" alt="7 ai portfolio projects to boost your resume” width=”100%” src=”https://technicalterrence.com/wp-content/uploads/2024/08/1722881311_564_7-AI-portfolio-projects-to-boost-your-resume.png”/><img decoding="async" src="https://technicalterrence.com/wp-content/uploads/2024/08/1722881311_564_7-AI-portfolio-projects-to-boost-your-resume.png" alt="7 ai portfolio projects to boost your resume” width=”100%”/>
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We have learned how to fine-tune large language models, but now we will fine-tune a generative ai model using personal photos. Stable Diffusion XL only needs a few images to fine-tune, and as a result, you can get optimal results, as shown above.
In this project, you'll first learn about Stable Diffusion XL and then fine-tune it on a new dataset using Hugging Face AutoTrain Advance, DreamBooth, and LoRA. You can use Kaggle for free GPUs or Google Colab. It comes with a guide to help you through every step of the process.
Conclusion
All projects mentioned in this blog were created by me. I made sure to include a guide, source code, and other supporting materials.
Working on these projects will give you valuable experience and help you build a strong portfolio, which can increase your chances of landing your dream job. I highly recommend everyone to document their projects on GitHub and Medium, and then share them on social media to attract more attention. Keep working and keep building – these experiences can also be added to your resume as real experience.
Abid Ali Awan (@1abidaliawan) is a certified data scientist who loves building machine learning models. Currently, he focuses on content creation and writing technical blogs on machine learning and data science technologies. Abid holds a Master's degree in technology Management and a Bachelor's degree in Telecommunication Engineering. His vision is to create an ai product using a graph neural network for students struggling with mental illness.