Top 10 Deep Learning Project Ideas For Beginners

Deep Learning and Artificial Intelligence have seen exponential growth over the past few years. Artificial intelligence and deep learning technologies have seen a surge in demand. They can be used to better understand customer perspectives, automate systems, and many other things. You can’t do much if you’re a Machine Learning enthusiast or a beginner in Machine Learning.

Deep learning is a way to communicate with the human brain. Deep learning, in short, is how computer programs learn from observations and make decisions based upon their experiences, much like the human brain. Deep learning is useful for speech recognition, natural language processing, and many other areas.

There are many areas that which deep learning architectures, such as deep neural networks, deep belief neural networks, and recurrent, can be used. This includes speech recognition and bioinformatics as well as computer visions and text recognition. Natural Language Processing, Machine Translation, and board game programming are all examples.

Deep learning is about developing computer systems that are capable of operating independently from human input. To understand deep learning in a deeper way, you must first try it out. You will gain experience by working on many deep learning projects.

We will be discussing some amazing deep learning projects for beginners in the Deep Learning Projects article. Once you have completed your project at a beginner level, you will be able to understand deep learning and then you can move on to more complex, hands-on projects.

The Benefits of Deep Learning

Technology can help solve some of the most difficult problems around the globe through deep learning.

• Deep learning algorithms are capable of performing feature engineering by themselves, increasing efficiency and accuracy.
• Deep learning algorithms can be used to extract insights from different data formats.
• Unstructured data can be transformed into amazing results by deep learning.
• Deep learning algorithms are able to detect anomalies and inconsistencies that human eyes would miss.
• Deep learning algorithms provide a high level of accuracy for medical tests that can be used to diagnose medical conditions.
• Deep learning algorithms are able to efficiently complete the same repetitive task with no downtime.

Also read: A Complete Beginner’s Guide to Deep Learning with Python

Framework to Deep Learning Projects

You have many options when it comes to choosing a framework for deep learning projects. A framework is a set of tools, compilers, and code libraries that can be used to create software or systems.

Here are some frameworks that you can use to help with deep learning projects.

1. PyTorch

PyTorch is best suited for large projects that often require customization. PyTorch uses Python programming language. PyTorch is a highly recommended framework for deep learning projects.

2. TensorFlow

Google Brain developed this deep learning framework. Tensorflow, an open-source platform for machine learning, is a platform that allows you to perform classification, regression, and neural networks.

TensorFlow is available as a framework for both GPUs and CPUs. To use this framework efficiently, the user must have a good understanding of Python and NumPy arrays. This framework is great for both beginners and advanced deep learning users.

3. Keras

This framework is a library of neural networks based on TensorFlow. This framework is intended to simplify machine learning modeling. It works on both CPUs and GPUs, similar to Tensorflow. This framework can be used in R, PlaidML, and Theano as well as CNTK ( Microsoft Cognitive Toolkit ).

The three frameworks mentioned are among the most popular for deep learning projects.

Gluon and Sonnet are just a few of the frameworks you can use for your deep learning projects. DL4J, ONNX, and MXNet are also available.

Ideas for Deep Learning Projects (For Beginners)

Here are some beginner-level deep learning projects you can start with and then move on to more advanced projects. Machine Learning will be the foundation of any beginner’s project.

1. Visual Tracking System

With the aid of a camera, a visual tracking system can be used to locate and track moving objects in a specified time period. This visual tracking tool can be used for security, surveillance and AR (augmented reality), traffic control as well as video editing and communication.

The visual tracking system employs deep learning algorithms to analyze the sequence of video frames and then it tracks the moving objects that are targeted between them.

2. Image Classification using CIFAR – 10 dataset

CIFAR – 10 is a collection that includes 60,000 images, each of which can be categorized into 10 different classes. This project aims to create an image classification model that can identify which class an input image belongs to. The test set includes 10,000 images and the training set has around 50,000 images. The training set is divided into five groups, with 10,000 images randomly arranged.

Deep learning relies heavily on image classification. These projects will expose you to exciting topics in deep learning that you won’t have the opportunity to explore.

3. Human Face Detection System or Human Face Detection

This is one of the most popular projects for beginners. Deep learning is a rapidly growing field that has led to a rapid increase in face recognition. Face recognition is a subset of object detection that focuses on the identification of meaningful objects.

Deep learning algorithms allow you to build models that detect the boundaries of the human face with high accuracy.

This project will help to understand and start object detection. By the end of it, you will be able to learn how to identify an object in an image.

4. Chatbot

Chatbots are becoming very popular these days. Chatbots save time and increase efficiency for organizations by speaking to customers. Chatbots are intelligent and can respond to human queries and questions in record time. Chatbots are able to interact with humans in the same way as humans.

You will only need to model a chatbot with IBM Watson’s API. This project will only require Python and Bluemix accounts on your computer.

5. Breast Cancer Classification

Cancer is the most deadly disease. Cancer is the most deadly form of cancer. It’s difficult to detect it early. It is important to be able detect cancer early in order to cure it. Histopathology images can be used to diagnose cancer in patients. Cancer cells are different from normal cells.

You can create an image classification model in your project to determine if someone has cancer.

Also read: Top 10 Easy Machine Learning Projects ideas For Beginners

6. Music Genre Classification System

Music can be used as a healer in the current world. It can help to calm the person and allow them to relax in their hectic schedules. This project idea allows you to create a model that classifies music genres using neural networks. This is one of the most exciting project ideas that will help you to improve your deep learning skills.

FMA (Free Music Archive) will be used during this project. FMA is an easy-to-access, open-source dataset that contains high-quality legal audios.

This project will require you to extract audio samples, such as spectrograms and MFCC, and then build a classification system for music genres. This project will allow you to build a model that automatically categorizes the music genre.

7. WaveGlow

This is a high-level project. WaveGlow, a flow-based generation network for speech recognition systems, was developed by NVIDIA. It can generate high-quality speech from Mel-spectrograms.

WaveGlow can only be used on a single network. It can also be trained using one cost function. The ultimate goal is to maximize the chances of training data.

8. DCGAN allows you to create human faces

DCGAN is for Deep Convolutional Generative Adversarial Network. DCGAN is an effective technique for creating images, audio, and texts that are indistinguishable from real-world data. This project uses random noise as the basis and then applies DCGAN to create human-like faces that don’t exist anywhere else in the world.

9. Driver Drowsiness Detection

This project will help you create a detection system that will detect signs of drowsiness and alert drivers to prevent them from getting into an accident. This project will require Python, OpenCV, Keras, and Keras.

10. Dog breed identification

This project will require you to create a distinguishing model that can be used to identify the breeds of dogs in the image. You can use Kaggle’s dog breed data for this project.

• Deep Learning Projects to Work on
• Detector
• Coloring an old B&W photo
• Digit Recognition System
• Image Caption Generator
• OpenCog
• IBM Watson
• Kaggle Titanic Prediction
• Prediction of House Prices
• Predict the next sequence
• Translator for Language

Conclusion

We don’t care what your level is, this article should have given you an overview of the deep learning projects that you can add to your resume.

These projects have real-world applications. Deep learning technology is still in its infancy. You can imagine the many variations you could bring into the projects that can help the world.