You have been learning programming languages, honing your machine-learning skills, and delving into the details of data points. Additionally, rather than just studying machine learning models, you are interested in creating your own.
Machine learning (ML) projects provide you a chance to put your newly acquired skills to use while also offering you something to include in your portfolio. As a consequence, they not only aid in your understanding of machine learning and data science but also enable you to show potential employers your true capabilities.
Here are a few machine learning project ideas to get you started that are appropriate for both beginners and more experienced ML students.
1. Automatic captioning of images
The project to enhance your skill must have to be automatic image captioning. You will gain knowledge of LSTM for natural language processing, CNN pre-trained models and computer vision. In the conclusion, you will create the application on Gradio or Streamlight to present your findings. A brief description of the image will be produced by the image caption generator.
To predict captions in several languages, you can build your deep-learning architecture or locate numerous projects that are similar online. The portfolio project's main goal is to tackle a special issue. The model architecture may be the same, but the dataset may differ. Your chances of landing a job will increase as you work with different data kinds.
2. Anticipated sales
How will a company's future sales be impacted by changing seasons, changing demographics, or governmental regulations?
The popular business technique of sales forecasting, which involves estimating the number of goods or services that a company will provide in the future based on pertinent historical data, is supported by questions like these. The use of machine learning by corporations to develop models that can predict sales with ever-increasing accuracy over earlier, less technologically advanced methods is therefore not surprising.
You will practice sales forecasting under this machine learning project using actual sales data given by Walmart. Your task is to forecast department-wide revenue for 45 Walmart locations spread across several geographies, while also accounting for significant seasonal discount times like Thanksgiving, Christmas, and the three major holidays (Labor Day, Thanksgiving, and Christmas).
3. Deep Learning Stock Price Forecasting
The popular project idea of forecasting using deep learning will teach you a lot about the analysis of time series data, data management, pre-processing, and neural networks in terms of time consumption.
The forecasting of time series is not easy. Understanding seasonality, holiday seasons, patterns, and everyday volatility is important. Simple linear regression may usually give you the best-performing model without the need for neural networks. However, in the high-risk stock market, even a 1% difference represents millions of dollars in the company's profits.
4. Create a recommendation system
Everyone has been in a situation where they are unclear about what to watch on a streaming site with an unlimited selection of videos. Do you watch that cheesy romantic comedy that is obviously from the early aughts or the futuristic anime series? Or perhaps you might watch the atmospheric noir from the 1940s?
Online platforms use sophisticated machine learning methods to generate personalized suggestions for consumers since they are mindful of the analysis paralysis that may be brought on by an abundance of possibilities. In reality, many of the most well-liked services available today, including Google, Netflix, and Xbox's Gamepass service, are based on recommendation systems.
5. Autonomous vehicle project
An advantage throughout the employment process comes from having a Reinforcement Learning project on your portfolio. The hiring manager will presume that you have a knack for solving problems and that you are willing to learn more about challenging machine-learning projects.
You should familiarise yourself with the basics of reinforcement learning before beginning the project because it differs significantly from many other tasks involving machine learning. You will test out multiple models and approaches throughout the project to enhance agent performance.
6. AI bot that can converse
Hugging Face TransformersAI for conversation is an enjoyable project. You will get knowledge of Facebook Blender Bot, processing conversational data, and developing chatbot user interfaces (API or Web App).
Hugging Face offers a vast library of pre-trained models and datasets, so you can essentially fine-tune the model on a new dataset. Your favorite movie character, a conversation between Rick and Morty, or a famous person you adore might all be considered.
In addition, you can modify the chatbot to suit your particular use case. Should a medical application arise. The chatbot understands the patient's emotions and requires technological knowledge.
7. Estimate home prices
Among the most significant and expensive life milestones is frequently purchasing a home. As a result, the housing and real estate sectors of the US (and global) industry are a few of the most important.
Although there are many other factors to consider when buying a home outside its financial value, many buyers want to know whether a certain house will be a wise investment over the long run. How much may your house be worth, for instance, if you were to sell it right now or after renovations?
Given the abundance of available public real estate data, housing price forecasting is an obvious application for machine learning. By creating an end-to-end machine learning system using Tensorflow 1. x and the AI Platform, you will learn how to apply machine learning to forecast housing prices in this self-guided lab from Google Cloud Training. To apply your knowledge to new projects, you'll also learn how to use the web for distributed learning and online prediction in general.
8. ML Project that can Identify Emotions
The face is a source of emotion, as painters, sculptors, and performers have known for thousands of years. The ancient sculptor who made the well-known statue Laocoon and his Sons employed twisted expressions on his victims' faces to represent their misery as they are attacked by snakes, in contrast to players in traditional Japanese Noh theatre who use light and shadow to depict smiles and frowns on otherwise immutable masks.
Thus, the face and its emotions provide yet another source of information that many humans frequently understand intuitively but that machines do not. However, the key features of faces that change as an expression do give machine learning models the chance to recognize at least some emotions. Work on a machine learning project that helps identify emotions.
There are numerous uses for machine learning, which is a burgeoning area. Building projects are the best ways to learn successfully, regardless of whether you are just commencing out or are already well familiar with the field. Work on machine learning projects to build your portfolio and hone your skills. With these fun projects, you can put your skills to the test and get ready for a career path as a machine learning specialist.
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