Top 25 Machine Learning Projects for Beginners in 2024

avcontentteam 11 Apr, 2024 • 11 min read

Introduction

Machine Learning projects offer you a promising way to kick-start your career in this field. Not only do you get to learn data science by applying it but you also get projects to showcase on your CV! Nowadays, recruiters evaluate a candidate’s potential by his/her work and don’t put a lot of emphasis on certifications. It wouldn’t matter if you just tell them how much you know if you have nothing to show them! That’s where most people struggle and miss out.!

You might have worked on several problems before, but if you can’t make it presentable & easy-to-explain, how on earth would someone know what you are capable of? That’s where these projects will help you. Think of the time you’ll spend on these machine learning projects like your training sessions. The more time you spend practicing, the better you’ll become! And don’t forget to apply your skills in machine language processing to make your projects even more effective and impactful.

Useful Information for Machine Learning Projects

To help you decide where to begin, we’ve divided Machine Learning Models list into 3 levels, namely:

  1. Beginner Level: This level comprises of data sets which are fairly easy to work with, and don’t require complex data science techniques. You can solve them using basic regression or classification algorithms. Also, these data sets have enough open tutorials to get you going. In this list, we have also provided tutorials to help you get started. You can also check out AV’s ‘Introduction to Data Science‘ course along with this!
  2. Intermediate Level: This level comprises of data sets which are more challenging in nature. It consists of mid & large data sets which require some serious pattern recognition skills. Also, feature engineering will make a difference here. There is no limit on the use of ML techniques; everything under the sun can be put to use.
  3. Advanced Level: This level is best suited for people who understand advanced topics like neural networks, deep learning, recommender systems etc. High dimensional datasets are also featured here. Also, this is the time to get creative. See the creativity best data scientists bring into their work and codes.

Do you want to Master Machine Learning Projects and Deep Learning? Here is a comprehensive program that covers the Machine Learning and Deep Learning Algorithms concepts in Detail along with 25+ real life Projects! Check out the complete list of Projects in the link below

Machine learning Projects

Beginner Level Machine Learning Project

1. Iris Data Set

iris_dataset_scatterplot-svg

This is probably the most versatile, easy and resourceful dataset in pattern recognition literature. Nothing could be simpler than the Iris dataset to learn classification techniques. If you are totally new to data science, this is your start line. The data has only 150 rows & 4 columns.

Problem: Predict the class of the flower based on available attributes.

Start: Get Data | Tutorial: Get Here

Let’s have a look at the Iris data and build a Logistic Regression Model in the Live Coding window below.

2. Loan Prediction Dataset

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Among all industries, the insurance domain has one of the largest uses of analytics & data science methods. This dataset provides you a taste of working on data sets from insurance companies – what challenges are faced there, what strategies are used, which variables influence the outcome, etc. This is a classification problem. The data has 615 rows and 13 columns.

Problem: Predict if a loan will get approved or not.

Start: Get Data | Tutorial: Get Here

Let’s have a look at the Loan data and build a Logistic Regression Model in the Live Coding window below.

3. Bigmart Sales Data Set

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Retail is another industry which extensively uses analytics to optimize business processes. Tasks like product placement, inventory management, customized offers, product bundling, etc. are being smartly handled using data science techniques. As the name suggests, this data comprises of transaction records of a sales store. This is a regression problem. The data has 8523 rows of 12 variables.

Problem: Predict the sales of a store.

Start: Get Data | Tutorial: Get Here

Let’s have a look at the Big Mart Sales data and build a Linear Regression Model in the Live Coding window below.

4. Boston Housing Data Set

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This is another popular dataset used in pattern recognition literature. The data set comes from the real estate industry in Boston (US). This is a regression problem. The data has 506 rows and 14 columns. Thus, it’s a fairly small data set where you can attempt any technique without worrying about your laptop’s memory being overused.

Problem: Predict the median value of owner occupied homes.

Start: Get Data | Tutorial: Get Here

5. Time Series Analysis Dataset

Time Series is one of the most commonly used techniques in data science. It has wide ranging applications – weather forecasting, predicting sales, analyzing year on year trends, etc. This dataset is specific to time series and the challenge here is to forecast traffic on a mode of transportation. The data has ** rows and ** columns.

Problem: Predict the traffic on a new mode of transport.

Start: Get Data  | Tutorial: Get Here

6. Wine Quality Dataset

This is one of the most popular datasets along data science beginners. It is divided into 2 datasets. You can perform both regression and classification tasks on this data. It will test your understanding in different fields – outlier detection, feature selection, and unbalanced data. There are 4898 rows and 12 columns in this dataset.

Problem: Predict the quality of the wine.

Start: Get Data | Tutorial: Get Here

7. Turkiye Student Evaluation Dataset

This dataset is based on an evaluation form filled out by students for different courses. It has different attributes including attendance, difficulty, score for each evaluation question, among others. This is an unsupervised learning problem. The dataset has 5820 rows and 33 columns.

Problem: Use classification and clustering techniques to deal with the data.

Start: Get Data | Tutorial: Get Here

8. Heights and Weights Dataset

This is a fairly straightforward problem and is ideal for people starting off with data science. It is a regression problem.  The dataset has 25,000 rows and 3 columns (index, height and weight).

Problem: Predict the height or weight of a person.

Start: Get Data | Tutorial: Get Here

If you’re new to the world of data science, Analytics Vidhya has curated a comprehensive course – ‘Introduction to Data Science’, aimed for beginners! We will cover the basics of Python, before moving to Statistics and finally going through various Modelling techniques, including advanced machine learning projects, deep learning models, and machine learning algorithms.

Intermediate Level Machine Learning Projects

1. Black Friday Dataset

black-friday

This dataset comprises of sales transactions captured at a retail store. It’s a classic dataset to explore and expand your feature engineering skills and day to day understanding from multiple shopping experiences. This is a regression problem. The dataset has 550,069 rows and 12 columns.

Problem: Predict purchase amount.

Start: Get Data | Tutorial: Get Here

2. Human Activity Recognition Dataset

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This data set is collected from recordings of 30 human subjects captured via smartphones enabled with embedded inertial sensors. Many machine learning courses use this data for teaching purposes. It’s your turn now. This is a multi-classification problem. The data set has 10,299 rows and 561 columns.

Problem: Predict the activity category of a human.

Start: Get Data | Tutorial: Get Here

3. Text Mining Dataset

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This dataset is originally from the Siam Text Mining Competition held in 2007. The data comprises of aviation safety reports describing problem(s) which occurred in certain flights. It is a multi-classification and high dimensional problem. It has 21,519 rows and 30,438 columns.

Problem: Classify the documents according to their labels.

Start: Get Data | Tutorial: Get Here

4. Trip History Dataset

trip-history-data

This dataset comes from a bike sharing service in the United States. This dataset requires you to exercise your pro data munging skills. The data is provided quarter-wise from 2010 (Q4) onwards. Each file has 7 columns. It is a classification problem.

Problem: Predict the class of user.

Start: Get Data | Tutorial: Get Here

5. Million Song Dataset

million-song

Did you know data science can be used in the entertainment industry also? Do it yourself now. This data set puts forward a regression task. It consists of 5,15,345 observations and 90 variables. However, this is just a tiny subset of the original database of data about a million songs.

Problem: Predict release year of the song.

Start: Get Data | Tutorial: Get Here

6. Census Income Dataset

us-census

It’s an imbalanced classification and a classic machine learning problem. You know, machine learning is being extensively used to solve imbalanced problems such as cancer detection, fraud detection etc. It’s time to get your hands dirty. The data set has 48,842 rows and 14 columns. For guidance, you can check this imbalanced data project.

Problem: Predict the income class of US population.

Start: Get Data | Tutorial: Get Here

7. Movie Lens Dataset

movie-lens-data

Have you built a recommendation system yet? Here’s your chance! This dataset is one of the most popular & quoted datasets in the data science industry. It is available in various dimensions. Here I’ve used a fairly small size. It has 1 million ratings from 6,000 users on 4,000 movies.

Problem: Recommend new movies to users.

Start: Get Data | Tutorial: Get Here

8. Twitter Classification Dataset

Mining Twitter Data

Working with Twitter data has become an integral part of sentiment analysis problems. If you want to carve a niche for yourself in this area, you will have fun working on the challenge this dataset poses. The dataset is 3MB in size and has 31,962 tweets.

Problem: Identify the tweets which are hate tweets and which are not.

Start: Get Data | Tutorial: Get Here

Advanced Level Machine Learning Projects

1. Identify your Digits Dataset

identify-the-digits

This dataset allows you to study, analyze and recognize elements in the images. That’s exactly how your camera detects your face, using image recognition! It’s your turn to build and test that technique. It’s a digit recognition problem. This data set has 7,000 images of 28 X 28 size, totalling 31MB.

Problem: Identify digits from an image.

Start: Get Data | Tutorial: Get Here

2. Urban Sound Classification

Sound Classification

When you start your machine learning and deep learning projects journey, you go with simple machine learning problems like titanic survival prediction. But you still don’t have enough practice when it comes to real life problems. Hence, this practice problem is meant to introduce you to audio processing in the usual classification scenario. This dataset consists of 8,732 sound excerpts of urban sounds from 10 classes.

Problem: Classify the type of sound from the audio.

Start: Get Data | Tutorial: Get Here

3. Vox Celebrity Dataset

Audio processing is rapidly becoming an important field in deep learning model, hence here’s another challenging problem. This dataset is for large-scale speaker identification and contains words spoken by celebrities, extracted from YouTube videos. It’s an intriguing use case for isolating and identifying speech recognition. The data contains 100,000 utterances spoken by 1,251 celebrities. This data cleaning is ideal for training deep learning models and machine learning algorithms focused on speaker identification and speech recognition tasks.

Problem: Figure out which celebrity the voice belongs to.

Start: Get Data | Tutorial: Get Here

4. ImageNet Dataset

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ImageNet offers variety of problems which encompasses object detection, localization, classification and screen parsing. All the images are freely available. You can search for any type of image and build your project around it. As of now, this image engine has more than 15 million images of multiple shapes sizing up to 140GB.

Problem: Problem to solve is subjected to the image type you download.

Start: Get Data | Tutorial: Get Here

5. Chicago Crime Dataset

chicago-crime

The ability to handle large datasets is expected of every data scientist these days. Companies no longer prefer to work on samples when they the computational power to work on the full dataset. This dataset provides you a much needed hands-on experience of handling large data sets on your local machines. The problem is easy, but data management is the key! This dataset has 6M observations. It’s a multi-classification problem.

Problem: Predict the type of crime.

Start: Get Data | Tutorial: Get Here

6. Age Detection of Indian Actors Dataset

This is a fascinating challenge for any deep learning enthusiast. The dataset contains thousands of images of Indian actors and your task is to identify their age. All the images are manually selected and cropped from the video frames resulting in a high degree of variability interms of scale, pose, expression, illumination, age, resolution, occlusion, and makeup. There are 19,906 images in the training set and 6,636 in the test set.

Problem: Predict the age of the actors.

Start: Get Data | Tutorial: Get Here

7. Recommendation Engine Dataset

Engine Dataset , Machine learning Projects

This is an advanced recommendation system challenge. In this practice problem, you are given the data of programmers and questions that they have previously solved, along with the time that they took to solve that particular question. As a data scientist, the model you build will help online judges to decide the next level of questions to recommend to a user.

Problem: Predict the time taken to solve a problem given the current status of the user.

Start: Get Data

8. VisualQA Dataset

Visual data qa dataset

VisualQA is a dataset containing open-ended questions about images. These questions require an understanding of computer vision and language. There is an automatic evaluation metric for this problem. The dataset has 265,016 images, 3 questions per image and 10 ground truth answers per question.

Problem: Use deep learning technique to answer open-ended questions about images.

Start: Get Data | Tutorial: Get Here

Conclusion

Out of the 24 datasets listed above, you should start by finding the one that matches your skillset. Say, if you are a beginner in Machine Learning Models, avoid taking up advanced level data sets from the get go. Don’t bite more than you can chew and don’t feel overwhelmed with how much you still have to do. Instead, focus on making step-wise progress.

Once you complete 2 – 3 projects, showcase them on your resume and your GitHub profile (very important!). Lots of recruiters these days hire candidates by checking their GitHub profiles. Your motive shouldn’t be to do all the projects, but to pick out selected ones based on the problem to be solved, domain and the dataset size. If you want to look at complete project solution, take a look at this article.

Frequently Asked Questions

Q1. How can I improve my data science skills?

A. You can improve your data science skills by keeping up with the new trends and techniques in the industry. Practicing different kinds of data science projects is another way of honing your skills. This article has listed 24 freely available projects of different difficulty levels for you to test and improve your skills.

Q2. What are some good machine-learning projects?

A. Here are some good machine-learning practice project datasets of different difficulty levels:
Beginner-level projects: Iris, loan prediction, big mart sales, time series evaluation, and student evaluation.
Intermediate-level projects: Human activity recognition, text mining, trip history, census income, and Twitter classification.
Advanced-level projects: ImageNEt, digit recognition, urban sound classification, age detection, and recommendation engine.

Q3. What are some beginner-level data science projects?

A. The Iris dataset is a great place to start at. Other beginner-level data science projects include loan prediction, big mart sales, time series evaluation, student evaluation, etc.

Q4.What are the 5 types of machine learning?

The five types of machine learning are:
Supervised learning
Unsupervised learning
Semi-supervised learning
Reinforcement learning
Self-supervised learning




avcontentteam 11 Apr 2024

Frequently Asked Questions

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Responses From Readers

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Demudu
Demudu 26 Oct, 2016

Fantastic

Mallikarjun
Mallikarjun 26 Oct, 2016

Thank You so much... :) I have been wondering, how to start with projects. This will help me out. I have done machine learning course of Prof. Andrew Ng. and I have good knowledge of statistics and R and Matlab. Please let me know, if any skill required to be a data scientist. Thank you again. :)

venugopal rao
venugopal rao 26 Oct, 2016

Great Collection.. All together in one place

Akash
Akash 26 Oct, 2016

Hey Manish, Good one. Do you have the 'R' equivalent for Boston housing and Big mart sales ? Thanks,

Femy
Femy 26 Oct, 2016

Do you have anything on operational risk or risk in general especially consumer credit risk

Sridevi
Sridevi 26 Oct, 2016

Hi Manish, Wonderful collection. Great resource for exploring ML. Thanks

Krishna
Krishna 26 Oct, 2016

Hi Manish, Can you please give some insights about the Knoctober data which was conducted recently?

Tesfaye
Tesfaye 26 Oct, 2016

Thank you Manish. These are wonderful project ideas. Please I would love to have sample solutions if/when you have them.

Funso Iyaju
Funso Iyaju 27 Oct, 2016

Hi Manish. Thanks for sharing this. It will help a lot in my love for data analytics

Prasanna Venktesh
Prasanna Venktesh 28 Oct, 2016

Hi what it takes to be a Datascientist. I don't have a powerful computer. whats the configuration I need. I'm a Software developer.. Do I need to do a course or can i learn on my own. Does working on here help me acquire the datascientist skills. Can You please tell me how can i enter data scientist role without losing my job. How to start my Datascientist career and what the employee seek.

RAMESH MAMILLA
RAMESH MAMILLA 29 Oct, 2016

Hello Manish, Thanks for sharing this information..am also want to build up my career in Analytics.. am facing lot of problems to getting a job..It would be a great article for the beginners..Thanks Bro..

Satya
Satya 30 Oct, 2016

This is Great Manish. I was able to get all the theoretical material for learning . But Application of those concepts in real life scenarios was always an issue. But I can say not anymore . Thanks to you. Regards, Satya

Palanisingh
Palanisingh 01 Nov, 2016

How to analyze the yearly data.

Varun
Varun 01 Nov, 2016

Hi Manish, Awesome job getting all the information together.

Partha sundar sahoo
Partha sundar sahoo 07 Nov, 2016

Hi manish sir I am an electrical engineer having 1.5yr experience. Iwant to switch from my sector to it. Is this big data a right choice for me. Please give your valuable advice.

sandip
sandip 21 May, 2017

Nice collection, great

Ujjayant
Ujjayant 28 May, 2017

Can you recommend a dataset/problem to practice clustering and PCA on ?

Rudy
Rudy 21 Jul, 2017

Hi, Great article and thanks for writing it. I tried checking the link for the Boston Housing Price data but it seems the data no longer is exist in the given link. Would request you to check once. Thanks, Rudy

Data Science Training in Hyderabad
Data Science Training in Hyderabad 25 Sep, 2017

Nice blog.Thanks for sharing great information about the Data Science projects to boost your knowledge and skills.

Anju
Anju 27 Sep, 2017

Your website is so well organized, perfect for an online self learner like me. Thank you team!

Prem Sharma
Prem Sharma 05 Oct, 2017

Very nice article to understand what exactly the Data Science is. And how can one make a grip on it. Do you have any similar example of Travel Domain (Destination Management Company) ? I want to do a project on this, since I am working in this domain. Thank you so much.

Owusu
Owusu 09 Oct, 2017

Thanks for sharing these valuable projects. They're much appreciated. I'm starting to work on projects to boost my knowledge and skills in Data Analytics.

Zabyn Ilam
Zabyn Ilam 16 Oct, 2017

wonderful website with lots of information and ideas. I was wondering, could you please help me out to get me idea about how to select a graduate level project on data analytics. I have interest in health data and newbie in programming. Any suggestion would be appreciated. I have 6 month to finish this. Thank you for the help. ZIlam

Divyush
Divyush 24 Oct, 2017

This is great work. Is there a tutorial or a detailed description of procedure for the project - Trip History Data Set . Number 4 under Intermediate level. Would be really nice if you could help. Thanks in advance

Shahnawaz
Shahnawaz 14 Nov, 2017

Fantastic Collection and most helpful, Appreciate your efforts

acreddy123@gmail.com
[email protected] 18 Nov, 2017

Hi team, i am new for data science need some documents and real time scenarios to learn it ,,i may need your help ,can some one help me on tat.

Sharvari GC
Sharvari GC 02 Dec, 2017

How long would it take me to complete all the 17 projects given that I work on them 5 hours a day? An estimate would help a lot

Barath Narayan
Barath Narayan 13 Dec, 2017

Hello Analytics Vidhya Content Team, Thank you so much for compiling these projects by level of proficiency. Wondering if the tutorials for the intermediate and advanced levels are going to be published in the near future. Best, Barath

Kavya
Kavya 18 Jan, 2018

Hello , i am planning to do data science projects which are mentioned in this blog. And i need help in downloading the datasets.. I tried couple of times clicking on Get data but i am not getting to download. Can someone help me ? Thanks.

Avishek
Avishek 28 Jan, 2018

This is great and helpful. Can you provide these explanations in downloadable pdf format?

Ajay Chander R.
Ajay Chander R. 29 Jan, 2018

excellent info.

Arpita
Arpita 09 Mar, 2018

Hey Manish, Amazing stuff! Before doing a deep dive into this data science field, I was wondering where I can find projects to work on once I start exploring. I am a new bee into this world. Please let me know which are sites or videos to start with. I wanna know about statistics and the basic maths involved to deal with problems. Also I would like to check in case we have solutions to cross check these problems. Keep doing good work! Love this website. Thanks, Arpita

Shakuntala
Shakuntala 13 Mar, 2018

Is there any way to download the data that we will be working on?

Akshay Kumar
Akshay Kumar 16 Mar, 2018

I have worked on the Boston housing dataset. Doing these kinds of projects is the best way to test our understanding of the subject. The dataset lets us do all kinds of preprocessing and then apply many machine learning algorithms for best accuracy. By far this is the best web-page present currently for data science. Thanks, AnalyticsVidhya.

Yash
Yash 26 Mar, 2018

These projects can be done using R or do we have to learn Python. I am more comfortable towards R.

pankaj
pankaj 17 Apr, 2018

Thanks for the data set. Can u share the bigdata project code also with GUI feature. So that we do the practice of coding also

xq
xq 24 Apr, 2018

I am a beginner and I started with the iris data. I have a question: the data has no training and test data. how to predict the class?Do I need to separate the data into two parts (training and test, and make the class of the test data to na? ) or there is some other data source? look forward to your response. thanks.

Binod Jung Bogati
Binod Jung Bogati 31 May, 2018

Great, I'm willing to work with new projects added here. Thanks for the new updates.

Manish
Manish 01 Jun, 2018

Simply excellent effort to summaries all details in one post .

Marcel
Marcel 01 Jun, 2018

People from Analytics Vidhya, Thanks again, for a great article. I keep coming back to your site.

Valentin
Valentin 04 Jun, 2018

Thanks for the wonderful post information above very useful guide helped me a lot.

Hari challa
Hari challa 06 Jun, 2018

Nice article useful to all

vipul vijay Dere
vipul vijay Dere 14 Jun, 2018

Hello All, Can anyone tell me how can I download this projects??

Hema Ramachandran
Hema Ramachandran 16 Jun, 2018

Hi, the tutorial link for NO. 5 'Time Series Analysis' is not opening. Can you kindly check that?

KEVIN
KEVIN 16 Jun, 2018

actually this gives you confident in approaching ML

Shalabh Nair
Shalabh Nair 18 Jul, 2018

Can anyone post the tutorial to the recommendation engine? It's missing here.

Kirill
Kirill 04 Aug, 2018

Hi, the tutorial link for NO. 1 ‘Iris Data Set’ is also not opening. Can you kindly check that?

Kalyani Sisodiya
Kalyani Sisodiya 08 Aug, 2018

Hi, I am going through UIC site for downloading data set but i am not able to download. can anyone tell me how to download that data set.. Thanks, Kalyani

Roma Jain
Roma Jain 03 Oct, 2018

Great resource ! thank you for sharing. I would like to know what are the pre-requisites to start the beginners level ? for somebody who is new to data science and does not have programming knowledge

Tanveer Fatima
Tanveer Fatima 22 Oct, 2018

Hi I have taken big data with no sql class in collage. And took 6 month crash course online . But still couldn’t able to find a job all need 3 or 5 years of experience. Please help me and guide me how I should be able to find job in USA.

kalyani
kalyani 11 Jan, 2019

Hello Team, Can I get sample answers for above questions? Please let me know

kalyani
kalyani 11 Jan, 2019

Hello team, Thanks for the post. Could you please provide sample answers for above questions? Please let me know. Thanks, Kalyani

Vijay
Vijay 05 Jan, 2024

Hi, I read your blog. It seems to be great. It has all the Data science information which we need !