Machine Learning Projects and Use Cases

Today, we are living in a technology-driven world. Of the many prevailing technologies, Machine Learning is the cutting-edge technology that rapidly dominates every business sector. That's because of the in-depth data-analyzing and prediction capabilities of Machine Learning models.

Know that Machine Learning (ML) is the subset of Artificial Intelligence. ML algorithms can analyze massive volumes of data and discover trends and patterns hidden in the data. Mainly, the impact of ML technology in predictive analysis is incredible. With the analytics and insights generated by ML algorithms, companies can prevent risks and make strong business decisions. As a result, they can boost productivity and enhance business outcomes.

As companies are embracing Machine Learning technology rapidly, there is an ever-growing demand for ML scientists and data analysts across the globe. You will encounter plenty of opportunities if you acquire sound knowledge of ML concepts and algorithms. No wonder big companies will hire you, providing excellent salary packages.

Are you wondering how to get expertise in ML technology?

No worries! We will help to gain mastery over Machine Learning in a smart way.

Thanks to Machine Learning projects! Working on Machine Learning projects is the best way to gain expertise in ML concepts and algorithms. If you practice on many Machine Learning projects, you will quickly learn the nuances of ML technology.

Okay! In this blog, we will discuss various Machine Learning projects ideas, their importance, the skills you will develop, and much more in greater detail.

Let’s get started!

Table of Contents - Machine Learning Projects

Why Machine Learning Projects? Prerequisites to Practice Machine Learning Projects Skills that you will gain through Machine Learning Projects Machine Learning Projects Beginners Experienced Machine Learning Real-time Project Examples Machine Learning Projects: Why are they so important? FAQs Conclusion

Why Machine Learning Projects?

As stated earlier, you can sharpen your skills in Machine Learning by thoroughly practicing Machine Learning projects.

Well! Let’s look into the reasons why learning Machine Learning projects is important.

Better career opportunities

Machine Learning is a cutting-edge technology that spreads like a virus everywhere. No matter whether it is a small, medium, or large scale company, they leverage Machine Learning technology to analyze their data and boom business. In return, it opens up numerous job opportunities for data science professionals across the globe.

Lack of talents

Although the invasion of ML in businesses brings up a lot of job opportunities for ML aspirants, there is still a huge shortage of correct-fit candidates. To put it another way, the gap between the expected skillset and the candidates' skillset is not tight. To become a complete ML professional, candidates must have sound mathematical knowledge, strong logical and analytical thinking, and other vital skills.

Attractive salary packages

Getting mastery over Machine Learning concepts and algorithms is not a cakewalk. It demands an enormous amount of focus and hard work. That’s why ML engineers and scientists are usually paid with lumpsum salary packages.

In short, sharpening your ML skills is essential to reach out to high-paid jobs and shine in your career. And the best way to hone your ML skills is by doing Machine Learning projects. This way, you can develop the required skillset to become a competent data analyst or engineer.

If you want to enrich your career and become a Machine Learning professional, enroll in " Machine Learning Training". This course will help you to achieve excellence in this domain.

Prerequisites to Practice Machine Learning Projects

No one will deny that solid preparation is the correct key to success. Before starting, you must know the prerequisites to practice Machine Learning project ideas.

Let’s list the prerequisites:

• Familiarity with statistical concepts such as mean, standard deviation, median, histogram, etc.
• Basic understanding of linear algebra, such as linear transforms, tensor rank, matrix multiplication, etc.
• Knowledge of probability concepts such as notation, random variables, probability distribution, etc.
• Proficiency in differential and integral calculus
• Understanding of neural network architectures    
• Basic coding skills in popular programming languages like MATLAB, Python, and C++.
• Sound problem-solving and critical thinking.
• Strong communication skills and teamwork

It is extremely important that if you lack one or more of the listed prerequisites, it is wise to equip the skills before starting the Machine Learning projects.

Skills that you gain through Machine Learning Projects

Once you complete working on various Machine Learning project ideas, you will gain many exceptional skills as listed below:

• Exposure to various ML algorithms. You will thoroughly understand data structure concepts like trees, queues, stacks, arrays, etc.
• Good project management and time management skills
• Proficiency in coding languages such as Python, Java, R, and C++.       
• Familiar with cloud computing and virtual machines.
• Exposure to natural language processing
• Mastery of data modeling and evaluation
• Thorough understanding of libraries and frameworks such as NumPy, Seaborn, Tensorflow, etc.

Sure! The above skills will undoubtedly make you a competent and ever-shining data engineer or data scientist.

Machine Learning Projects

As discussed earlier, practicing Machine Learning projects help to sharpen your skills in Machine Learning. Once the skills come in handy, you can easily breeze through the Machine Learning tasks.

Keeping that in mind, MindMajix content specialists compiled two sets of Machine Learning projects in this section – one is Machine Learning projects for beginners, and another is Machine Learning projects for experienced. If you go through the Machine Learning project ideas, you will ultimately understand the goals and outcomes of the Machine Learning projects.

You can start working on the Machine Learning project ideas from the beginning if you are a novice. If you are an experienced learner, the advanced Machine Learning projects will be hugely helpful.

Let’s keep on reading!

Machine Learning Projects for Beginners

As a beginner, you can find the following Machine Learning projects for beginners. These projects will be highly beneficial to get familiar with various Machine Learning algorithms and models.

• Home value predictor

If you are going to buy a home or looking for a rental home, you can use this ML-based home value predictor to evaluate the home's worth. The ML algorithms employed in this predictor consider many vital factors to predict home value. The factors can be the average income of buyers, the number of hospitals and schools around the home, statistics of crime in that home area, and so on.

By completing this Machine Learning project, you will get the opportunity to learn XGBoost algorithms used to make home value predictions.

• Stock Price Predictions

In this ML project, you will create a Machine Learning application to predict stock prices. You will make stock price predictions using the volatility indices, stock price history, etc.

By completing this Machine Learning project, you will learn to make stock price predictions effortlessly for the next few months. Also, you will gain mastery over handling a massive volume of data through this project. Note that you can collect the sample dataset needed for this project from Quantopian.

• Sales Prediction

This is one of the helpful Machine Learning project ideas for beginners. In this ML project, you will construct a Machine Learning application that will analyze a massive amount of sales data and thus make effective forecasting.

By working on this project, you will get exposure to regression models used to make forecasting.

• Wine Quality Predictions

Shopping for wines is an intriguing task. You must have some expertise to figure out the original and quality wines. If not, you might end up buying poor-quality wines. Don't worry if you can't help identify with quality wines. An ML-based wine quality predictor will help you to find high-quality wines.

In this Machine Learning project, you will create an ML-based wine quality predictor to pick out the good quality wines. This predictor takes into account the age and price of wines to validate the quality of wines. By working on this project, you will gain proficiency in regression models, data visualization, and many more. Mainly, you will get exposure to R programming by doing this project.

• Human activity recognition with smartphones

This Machine Learning project helps to create a Machine Learning application to track human activities closely. The fitness data of different persons can be used for this project to perform effective analysis. The important thing is that the more you gather data, the more accurate the results will be. As a next step, you should input the fitness data into the Machine Learning classification models to predict the future activities of the persons.

By practicing this Machine Learning project, you will learn about inertial sensors that help to collect data from humans. Besides, you will get proficient with multi-classification problems by doing this project.

• Music Recommendation System

In this project, you will build a music recommendation system to tell users what music to listen to next. This is done based on analyzing the users’ preferences, interests, and history of listening. By working on this Machine Learning project, you will learn to use popular programming languages like Python and R.

• Time-series based Stock prices predictor

This is another interesting Machine Learning project in which you will create a stock prices predictor to foretell companies' stock prices. The stock prices over a time span are taken into account for analysis. This way, the predictor analyses the company's performance and predicts future stock values.

• Iris flowers Classification

This is one of the must-to-do Machine Learning projects for beginners. In this project, you will develop an ML application to classify datasets. By practicing this Machine Learning project, you will learn to handle large volumes of data effortlessly.

This Machine Learning project will teach you about many time-series forecasting mechanisms, such as exponential smoothing, ARIMA, and much more.

Machine Learning Projects for Experienced

As an experienced learner, you can find the following advanced Machine Learning projects that will assist to polish your skills in Machine Learning.

Let’s see them in detail!

• Finding frauds when tracking imbalanced data

Detecting fraud is a must-do activity for the finance and banking sectors. In recent years, ML-based fraud-detection mechanisms have played a significant role in identifying fraud. When dealing with imbalanced data, it is essential to check for fraud. That’s because the probability of fraud is high with imbalanced data.

By working on this Machine Learning project, you will get the opportunity to learn robust strategies such as undersampling, oversampling, or combined.

• Bitcoin price predictor

In this project, you will develop a price predictor to forecast Bitcoin prices. The predictor performs exploratory data analysis to identify trends and patterns in the bitcoin prices data.

By practicing this Machine Learning project, you will get exposure to Pandas libraries, XGBoost algorithms, NumPy arrays, and much more. Mainly, you will get expertise in Python programming by doing this project.

• Market basket analysis

In this project, you will build an application to identify similar items based on customers' shopping history. For instance, if a customer buys certain items, this application predicts similar items and recommends them to the customer.

By completing this Machine Learning project, you will get familiar with the Apriori algorithm with which you can forecast customers' buying behavior.

• Enron Investigation ML Project

Enron is a company that no longer operates since 2000. But it left a large amount of data to learners for making data analysis. You can find over five lakhs of emails created by Enron employees. So you can best use this data for learning purposes.

• Handwritten Character Recognition

It is yet another complex Machine Learning project. Recognizing handwritten characters is not accurate if we employ traditional recognition methods. You can overcome this setback with the help of ML models. First, you must precisely label the data that has handwritten characters. Next, you must apply the ML algorithms to analyze the data and recognize the handwritten characters.

By working on this Machine Learning project, you will get exposure to Convolutional Neural Networks. Also, you will get familiar with neural network libraries like Keras and Tensorflow, and so on.

Machine Learning Real-time Projects Examples

If you work on the following real-time Machine Learning projects intensely, it will help to polish your skills in machine learning brighter.

• Sign language recognition system
• Box office revenue prediction
• Music genre classification
• Breast cancer prediction
• Fake news detection project
• Loan prediction using ML
• Uber data analysis
• Customer segmentation using ML
• Xbox game prediction
• Image segmentation with ML

Machine Learning Projects: Why are they so important?

Undeniably, you can improve your knowledge of Machine Learning in multiple ways. However, practicing Machine Learning projects is the best way to hone one’s skills in Machine Learning.

Let’s put some more light into it!

• Knowledge of Multiple Domains

Machine Learning is the technology that invades every domain nowadays. From healthcare to banking to image/text recognition, Machine Learning aids dig out valuable insights from mountains of data. So completing Machine Learning projects will provide you with a broad spectrum of knowledge almost in every domain.

• Tracking customer and product behavior

With the help of Machine Learning applications, you can tightly track customers' behavior and interests. Not only that, the applications help to analyze product performance and sales data. They dig out crucial insights and information with which businesses can boost their productivity. So by completing Machine Learning projects, you will learn how to handle business data and drives up business growth.

• Tapping with the latest innovations

ML-based smart cars can figure out the partially visible objects on roads and immediately alert drivers. Similar to this, virtual assistants can recognize speeches with the assistance of advanced ML algorithms. Thus, you get exposure to the latest technologies and innovations by working on Machine Learning projects.

• Getting Hired by Big Companies

Business Giants like Facebook, Uber, Google, etc., embrace Machine Learning to enhance their business operations. If you gain mastery over Machine Learning projects, the chance of getting hired by these companies is not a big deal.

At a glance, practicing Machine Learning projects allow you to gain knowledge in numerous domains. Also, you will get familiar with analyzing data with robust ML algorithms. Most importantly, Practicing Machine Learning projects makes you a smart ML engineer or data scientist.

Machine Learning FAQs

1. List out some popular Machine Learning projects.

Below are some of the popular machine-learning projects.

• Sentiment analyzer
• Handwritten character classification
• Sales prediction Machine Learning project
• Movie ticket pricing system
• Human activity recognition through the smartphone

2. What do you mean by a Machine Learning Project?

A machine Learning project is a tool that helps to get expertise with Machine Learning concepts. In a way, a Machine Learning project serves as the stepping stone to level up your skillset on Machine Learning.

3. How to start doing a Machine Learning project?

Below is the step-by-step procedure for doing a machine learning project.

• First, collect data from reliable sources
• Clean, preprocess and label the dataset
• Next, choose the suitable ML model
• Train the model with the dataset
• Evaluate the model

Make predictions and infer insights from the results.

4. What is the salary range of freelance Machine Learning engineers?

Freshers can get a salary package of 5.4 lakhs on average. Candidates with a few years of experience can get an average salary package of up to 8.4 lakhs.

5. Name a commonly used real-time example of a Machine Learning model.

The movie recommendation system is one of the familiar Machine Learning implementations. This ML system provides movie recommendations to users based on their previous watching history and preferences.

6. What is the programming language used in Machine Learning?

Python and R are the programming languages widely used in Machine Learning.

7. Mention any one simple Machine Learning model?

This project helps decide whether to wear a rain jacket based on the weather conditions. A linear regression-based ML model is used in this project.

8. Is it tough to learn Machine Learning?

Not at all! Practicing a Machine Learning project is a piece of cake if you groom the mathematical and statistical skills.

9. What would be the future of Machine Learning?

The future of Machine Learning technology is highly promising. Most business domains, such as healthcare, automotive, entertainment, sales and marketing, are adopting Machine Learning on large scales. So ML has a bright future, without a doubt.

10. Does coding skills necessary to learn Machine Learning?

Yes. Coding skills in popular programming languages such as Python and R are necessary to work with advanced Machine Learning projects. Otherwise, you cannot surpass some basic-level Machine Learning projects.

Conclusion

Now, it’s time to conclude! You might have got a basic understanding of Machine Learning by going through the various Machine Learning projects for beginners and the experience addressed in this blog. If you want to level up your skillset in Machine Learning, you must work on real-time Machine Learning projects. It will provide you with an excellent hands-on experience in Machine Learning.

Above all, if you want to make a breakthrough in enriching your skills in Machine Learning, you must attend professional training. Register for a Machine Learning course in MindMajix, and get certification. It will advance you in the job competition and help quickly ramp up your career growth.