Machine Learning Projects for Beginners

Sources

In this article, I will show you 5 beginner level Machine Learning Projects for Beginners. All the projects are solved and explained. If you are new to Machine Learning and want to improve yourself more before getting into projects you can go through my free course here.

If you have already gone through some valuable topics of machine learning and want to get started with some projects, then here are some projects for you to get started with Machine Learning Projects.

Jobs in AI

5 Machine Learning Projects for Beginners

Creating your own Algorithms:

If you are using Scikit-Learn, you can easily use a lot of algorithms that are already made by some famous Researchers, Data Scientists, and other Machine Learning experts. Have you ever thought of building your algorithm instead of using a module like Scikit-Learn?

All the Machine Learning Algorithms that Scikit-Learn provides are easy to use but to be a Machine Learning Expert in a brand like Google and Microsoft, you need to build your algorithms instead of using any package so that you could easily create an algorithm according to your needs.

In this project, I will show you how you can easily create your algorithms instead of using any package like Scikit-Learn provided with Python. I will create a Linear Regression Algorithm using mathematical equations, and I will not use Scikit-Learn in this task. You can see the complete project here.

Trending AI Articles:

1. Machine Learning Concepts Every Data Scientist Should Know

2. AI for CFD: byteLAKE’s approach (part3)

3. AI Fail: To Popularize and Scale Chatbots, We Need Better Data

4. Top 5 Jupyter Widgets to boost your productivity!

Binary Classification Model:

Binary Classification is one of the most frequently studied problems in machine learning projects and real-life scenarios and it has led to a large number of important algorithmic and theoretic developments over the past decades. In its simplest form, it reduces to the question: given a pattern x drawn from a domain X, estimate which values an associated binary random variable y ∈ {±1} will assume.

For instance, in pictures of apples and oranges, we might want to state whether the object in question is an apple or an orange. Equally well, we might want to predict whether a homeowner might default on his loan, given income data, his credit history, or whether a given e-mail is spam or ham. The ability to solve this basic problem already allows us to address a large variety of practical settings. See Full Project on Binary Classification.

Multiclass Classification Model:

Multiclass Classification is the logical extension of binary classification. The main difference is that now y ∈ {1, . . . , n} may assume a range of different values. For instance, we might want to classify a document according to the language it was written in (English, French, German, Spanish, Hindi, Japanese, Chinese, . . . ). The main difference to before is that the cost of error may heavily depend on the type of Regression estimation.

For instance, in the problem of assessing the risk of cancer, it makes a significant difference whether we misclassify an early stage of cancer as healthy (in which case the patient is likely to die) or as an advanced stage of cancer (in which case the patient is likely to be inconvenienced from overly aggressive treatment). You can see the full project here.

Natural Language Processing on WhatsApp Chats:

Natural Language Processing or NLP is a field of Artificial Intelligence which focuses on enabling the systems for understanding and processing the human languages. In this project, I will use Natural Language Processing to analyze my WhatsApp Chats. For some privacy reasons, I will use Person 1, Person 2 and so on in my WhatsApp Chats. See Full Project here.

Image Filtering with Machine Learning:

Image filtering is also one of the amazing ideas for Machine Learning projects. It used to enhance the edges in images and reduce the noisiness of an image. This technology is used in almost all smartphones. Although improving an image using the image filtering techniques can help in the process of object detection, face recognition and all tasks involved in computer vision. In this project, I will take you through some Image Filtering methods with Machine Learning using Python. See Full Project here.

I hope you liked this article on Machine Learning Projects for Beginners. Feel free to ask your valuable questions in the comments section below. You can also follow me on Medium to cover every topic of Machine Learning.

Don’t forget to give us your ? !


Machine Learning Projects for Beginners was originally published in Becoming Human: Artificial Intelligence Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.

Via https://becominghuman.ai/machine-learning-projects-for-beginners-6cea2b89e7ce?source=rss—-5e5bef33608a—4

source https://365datascience.weebly.com/the-best-data-science-blog-2020/machine-learning-projects-for-beginners

Published by 365Data Science

365 Data Science is an online educational career website that offers the incredible opportunity to find your way into the data science world no matter your previous knowledge and experience. We have prepared numerous courses that suit the needs of aspiring BI analysts, Data analysts and Data scientists. We at 365 Data Science are committed educators who believe that curiosity should not be hindered by inability to access good learning resources. This is why we focus all our efforts on creating high-quality educational content which anyone can access online.

Leave a comment

This site uses Akismet to reduce spam. Learn how your comment data is processed.

Design a site like this with WordPress.com
Get started