Following the growth of ‘smart’ technologies, Machine Learning (ML) has become an emerging technology. The global ML market size is forecasted to expand from $26.03 billion in the year 2023 to $225.91 billion by the year 2030, implying its significant rise and expansion across domains.
From healthcare to manufacturing, ML’s presence is indomitable, strengthening digital devices to assist humans with their needs better every day. Considering this growth of Machine Learning, tech aspirants can visualise a beaming career in the relevant domain.
Let us take you through some of the best Machine Learning projects for beginners to get started!
1) Recognition of Handwritten Characters
Software applications find it challenging to understand the text contained in a specific image. This is especially challenging if the image contains handwritten text. However, this Machine Learning project solves these concerns because it provides you access to labelled datasets. The dataset comprises labels and handwritten characters that inform you about what text the particular image contains. The project uses ML algorithms to train a model which can be employed to make predictions in the future.
2) Personality Prediction
With this project, you can read posts of other users online and can comprehend their personalities. It intends to find the Myers-Briggs personality of an individual. To predict people’s personalities, this ML model uses the kinds of posts people upload on social media.
3) Digit Recogniser
Do you want to enhance your computer vision skills? If yes, then you can work on this ML project. It involves creating an ML algorithm that identifies the identified digits from a huge dataset that consists of other handwritten images. Essentially, the dataset contains a myriad of images that may include some handwritten digits too.
4) Music Genre Classification
This ML project analyses audio data and audio files. ML algorithms can’t easily learn from audio. With this project, you can build a music genre classification model based on how it sounds like for tasks involving music classification. The corresponding model accesses audio files as the input and label or classify them into a music genre like jazz, rock, pop, etc.
5) Stock Price Prediction
Based on the success and failure of the companies, the stock markets represent corresponding highs and lows. It is challenging to predict the stock market; however, this project comes in handy in such a scenario. It lets you predict future stock price returns depending on past stock market data such as opening price, closing price, calculated returns, trading volume, etc.
6) Automatic License Number Plate Recognition System
The aforementioned project aims to identify license number plates. You need to use OpenCV to recognise number plates. It uses Python py-tesseract to extract digits and characters from the number plates. Essentially, Python py-tesseract reads image types and extracts the information existing in the image.
7) Breast Cancer Prediction
This ML project uses a dataset to predict the odds that a breast tumour is benign or malignant. It predicts breast cancer based on different factors like the number of bare nuclei, lump thickness, and mitosis. Moreover, it uses R programming in the further stages. If you want to strengthen ML skills and practice R programming simultaneously, you can consider working on this project.
8) Housing Prices Prediction
This project aims to predict the final price of a house. For this prediction, the model uses factors like a house’s area, location, land counter, included facilities, utilities, roof materials, garage quality, proximity to the market, etc.
9) Coupon Purchase Analysis
Businesses use coupon marketing to engage customers to purchase their predicts. They can determine customers’ interest and future behaviour in coupons by assessing customers’ reactions to various types of coupons.
The project uses ML algorithms, Data Visualization tools, and Deep Learning techniques to understand the customers’ usage behaviour and their inclination for specific types of coupons. Consequently, it leads to the creation of a recommendation system that generates customer-specific coupons. Thus, this project ultimately benefits businesses with increased sales and revenue.
10) Autocorrect Keyboard using ML and Python
The term ‘autocorrect’ relates to NLP (Natural Language Processing) in the Machine Learning context. The project mentioned above corrects your errors and spellings while typing. The corresponding autocorrect model is trained to do corrections when the user inputs the text.
It also pinpoints the most related and comparable words. Using NLP, it compares the typed words and the words stored in the vocabulary dictionary.
11) Sorting Specific Tweets on Twitter
This project filters tweets comprising particular words. It lets programmers develop an algorithm that inputs scraped tweets that run through a natural language processor. Subsequently, it determines the matched specific information, themes, etc.
12) Inventory Demand Forecasting
The companies that provide products must ascertain that they have a sufficient amount of products to satisfy their customers. Thus, it is vital to roughly estimate the efforts required to meet the inventory demand. You can implement this ML project using Boosting, Bagging, Gradient Boosting Machine (GBM), Support Vector Machines, XGBoost, and more.
13) Retail Price Optimization
To optimise the retail price, this ML project trains an ML model competent in automatically pricing products just like how humans price them. The corresponding models accept historical sales data, different features of the products, images, and textual details to determine the pricing rules. There is no human intervention. Hence, retailers benefit from live pricing to maximise revenue as well as maintain profit margins.
14) Credit Risk Prediction
This ML project lets you analyse a portion of the customer database to determine the number of customers who are likely to not pay in the upcoming 2 years. Various machine learning models can be employed to predict customers that default on a loan. The corresponding data helps the banks to cancel credit lines for deceptive customers or reduce the card’s credit limit to curtail losses. Also, these models help banks determine which customers are to be provided with a credit card.
15) Driver Demand Forecasting
Two of the most demanding services on a daily basis are food delivery and ride-sharing. The smooth operation of these services depends on the drivers’ availability. To forecast the driver demand, this ML project transforms a time series problem into a supervised ML problem. It performs exploratory analysis on the time series to recognise patterns. ACF (Auto-Correlation Function) and PACF (Partial Auto-Correlation Function are implemented to evaluate time series. Spot testing is performed after preparing the training model.
Conclusion
Working on any of the mentioned machine learning project ideas will brush up on your ML basics, helping beginners to understand the significance and practical implementation of ML as they work on real-life projects.
Besides exploring basic ML projects, if you are interested in gaining more insights into machine learning and AI, check out Artificial Intelligence and Machine Learning course provided by Eduonix Learning Solutions. It is designed considering beginners willing to land an excellent career in AI-ML. It covers basic tools and technologies, including NumPy, Python, SciPy, Matplotlib, Pandas, and more.
Learning the concepts covered in this course helps you beg the six-figure salary paycheck. Moreover, you get unlimited lifetime access and updates with cutting-edge AI & ML technologies!
