Must-Watch Deep Learning Project Ideas for Beginners and Professionals

5 min readDec 17, 2021


Deep Learning project ideas using (AI and ML)
Deep Learning project ideas using (AI and ML)

One thing that can surely be concluded from recent times in the technology world is that despite being a new technological advancement, DL scope is increasing and growing exponentially. For the newbies, DL is a subdomain under machine learning algorithm (which is a subdivision of data science) and it aims to mimic the biological neuron network (BNN), i.e., of the human brain.

While the beginnings of Deep Learning date back to the 1950s, it is just with the progression and reception of Artificial Intelligence and Machine Learning that it went into the spotlight. In this way, in case you are an ML beginner, everything thing you can manage is to work on some Deep learning project ideas.

Deep Learning project ideas

12 Sigma’s Lung Cancer detection algorithm

12 Sigma has fostered an AI calculation that can diminish indicative mistakes related to lung cancer in its beginning phases and identify indications of lung cancer a lot quicker than conventional methodologies.

As per Xin Zhong, the CEO of Sigma Technologies, normally traditional cancer recognition practices set aside an effort to identify lung cancer. Be that as it may, 12 Sigma’s AI calculation framework can diminish the determination time, prompting a superior pace of endurance for lung cancer patients.

By and large, specialists analyze lung cancer via cautiously looking at CT examine pictures to check for little knobs and order them as harmless or threatening. It can assume control of more than ten minutes for specialists to outwardly review the patient’s CT pictures for knobs, in addition to extra an ideal opportunity for characterizing the knobs as harmless or dangerous.

Obviously, there consistently stays a high chance of human blunders. 12 Sigma keeps up with that its AI calculation can examine the CT pictures and characterize knobs inside two minutes.

Google Brain

This is one of the brilliant profound learning project thoughts. The Google Brain project is Deep Learning AI research that started in 2011 at Google. The Google Brain group drove by Google Fellow Jeff Dean, Google Researcher Greg Corrado, and Stanford University Professor Andrew Ng meant to bring Deep Learning and Machine Learning out from the limits of the lab into this present reality. They planned one of the biggest neural organizations for ML — it included 16,000 PC processors associated together.

To test the capacities of a neural organization of this enormous size, the Google Brain group took care of the organization with arbitrary thumbnails of feline pictures sourced from 10 million YouTube recordings. In any case, the catch is that they didn’t prepare the framework to perceive what a feline resembles. Be that as it may, the wise framework left everybody amazed — it showed itself how to distinguish cats and further proceeded to collect the elements of a cat to finish the picture of a cat.

The Google Brain project effectively demonstrated that product-based neural organizations can impersonate the working of the human cerebrum, wherein every neuron is prepared to recognize specific articles.

IBM Watson

One of the most astounding instances of Machine Learning and Deep Learning is IBM Watson. The best part of IBM Watson is that it permits Data Scientists and ML Engineers/Developers to team up on an incorporated stage to improve and mechanize the AI life cycle. Watson can improve, speed up, and oversee AI arrangements, in this manner empowering organizations to tackle the capability of both ML and Deep Learning to help business esteem.

IBM Watson is Integrated with the Watson Studio to engage cross-utilitarian groups to convey, screen, and advance ML/Deep Learning models rapidly and productively. It can naturally produce APIs to help your engineers fuse AI into their applications promptly. In addition, it accompanies instinctive dashboards that make it advantageous for the groups to oversee models underway flawlessly.

Music genre grouping framework

This is one of the fascinating profound learning project thoughts. This is a brilliant venture to support and further develop your profound acquiring abilities. You will make a profound learning model that utilizes neural organizations to order the class of music naturally. For this undertaking, you will utilize an FMA (Free Music Archive) dataset. FMA is an intelligent library involving superior grade and legitimate sound downloads. It is an open-source and effectively available dataset that is incredible for a large group of MIR undertakings, including perusing and sorting out tremendous music assortments.

Nonetheless, remember that before you can utilize the model to order sound records by class, you should separate the applicable data from the sound examples (like spectrograms, MFCC, and so forth)

Face recognition framework

This is one of the great profound learning project thoughts for novices. With the development of profound learning, facial acknowledgment innovation has additionally progressed immensely. Face acknowledgment innovation is a subset of Object Detection that spotlights on noticing the occurrence of semantic articles. It is intended to follow and imagine human countenances inside computerized pictures.

In this profound learning project, you will figure out how to perform human face acknowledgment progressively. You need to foster the model in Python and OpenCV.

Visual global positioning framework

A visual global positioning framework is intended to follow and find moving object(s) in a given time span by means of a camera. It is a helpful instrument that has various applications like security and observation, clinical imaging, increased reality, traffic signal, video altering and correspondence, and human-PC communication.

This framework utilizes a profound learning calculation to examine consecutive video outlines, after which it tracks the development of target objects between the edges. The two central parts of this visual global positioning framework are:

  • Target portrayal and localization
  • Separating and data affiliation


DeepMimic is a “model directed Deep Reinforcement Learning of Physics-based person abilities.” all in all, it is a neural organization prepared by utilizing support figuring out how to recreate movement caught developments by means of a mimicked humanoid, or some other actual specialist.

The working of DeepMimic is really basic. To begin with, you need to set up a recreation of what you wish to vitalize (you can catch somebody making explicit developments and attempt to emulate that). Presently, you utilize the movement catch information to prepare a neural organization through support learning. The contribution here is the design of the arms and legs at various time focuses while the prize is the distinction between the genuine article and the reproduction at an explicit time focuses.

Final Words

I hope this piece was able to successfully educate all you wonderful viewers about the various DL project ideas. If you are deep into DL and thrive to make a career in it, start with a data science course, and that too from trusted institutions.

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