TensorFlow is an open-source software library dedicated to artificial intelligence (AI) and machine learning (ML). Through it, developers create large-scale neural networks. This helps engineers and developers work on machines and programs capable of image recognition, vehicle detection, image processing, and even text-based applications.
If you’re hoping to sharpen your skills with TensorFlow and grow your portfolio, this article is for you. It includes the best projects for beginner, intermediate, and advanced TensorFlow users to help you expand your knowledge of this framework. These projects are often issued in TensorFlow bootcamps, online courses, or as part of a degree. You can also pursue them as part of your self-study.
5 Skills That TensorFlow Projects Can Help You Practice
The most significant advantage of building TensorFlow projects is the number of skills you will leverage. Whether you are a beginner, intermediate or advanced user, you will increase your proficiency and confidence using this open-source library. Below are five of the skills that these TensorFlow projects will help you practice.
- Artificial Intelligence. TensorFlow will expose you to varied skills in artificial intelligence. The library will take you through applications for speech recognition, natural language processing, and machine vision.
- Machine Learning. As TensorFlow is a machine learning tool, you can expect to delve deeper into this field’s core concepts. You will touch on convolutional neural networks, natural language processing, neural network architecture, reinforcement learning, and applied mathematics.
- Coding. TensorFlow projects will help you improve your coding skills. The platform will expose you to programming languages such as C++, CUDA, and Python.
- Deep Learning. Deep learning is a branch of machine learning that deals with recurrent neural networks. This entails building projects that mimic the human brain. In building the projects, you will get more familiar with computer science, front end UI technology, and cloud computing platforms.
- Data Science. TensorFlow is used by data scientists to create data flow graphs. They rely on the framework to showcase how data moves in a graph. Through building these projects, you will develop key data science knowledge and skills.
Best TensorFlow Project Ideas for Beginners
If You are just getting started with TensorFlow, take a look at the list we’ve compiled with beginner-friendly TensorFlow project ideas to help you develop a strong foundation. These are simple and relatively easy projects to catapult you into the industry.
Predicting House Prices with Regression using TensorFlow
- TensorFlow Skills Practiced: Deep Learning, Artificial Neural Network, Keras
Coursera offers a two-hour guided project to help students develop skills in neural networks and solve complex machine learning problems. In the program, you will learn how to utilize Keras and TensorFlow as its backend. It also features a step-by-step guide to ensure you are on the right track.
- TensorFlow Skills Practiced: Artificial Intelligence, Machine Learning, Deep Learning
You can utilize your knowledge in TensorFlow to build an image recognition project. The library has plenty of resources to help you see your project to completion. Image recognition is often used by security companies or general companies which require face detection at their entrances. You can also opt for Keras. To complete the project, you must know artificial neural networks.
- TensorFlow Skills Practiced: Machine Learning, Deep Learning, Artificial Intelligence
This is another TensorFlow-based project involving language processing. You can use the TensorFlow library to incorporate this text-to-speech converter that infers patterns from datasets of labeled speech. You can also improve the hardware functions by using Raspberry Pi, Arduino, and GPU servers.
- TensorFlow Skills Practiced: Machine Learning
This project is reliable in identifying a particular object amongst thousands of objects. It utilizes the TensorFlow ImageNet classifier that helps pinpoint a particular object correctly.
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Optical Character Recognition using TensorFlow
- TensorFlow Skills Practiced: Artificial Intelligence, Machine Learning
In this project, you will learn how to extract text from images. In order to do this, you’ll need to become familiar with edge detection, document rewarding, and optical character recognition functionalities available in the TensorFlow library.
Best Intermediate TensorFlow Project Ideas
Intermediate TensorFlow project ideas will help you develop sound skills and knowledge of the framework. The higher difficulty level will challenge you to think beyond ordinary mobile applications. These intermediate projects are great to boost your portfolio.
Basic Sentiment Analysis with TensorFlow
- TensorFlow Skills Practiced: Deep Learning, Artificial Neural Network, Document Classification
This project involves using Keras and TensorFlow as its backend. You’ll work on the creation and training of a neural network model capable of basic sentiment analysis applied to movie reviews. Your trained neural network will be able to distinguish whether the reviews are positive or negative by analyzing the text.
SIGHT: For the Blind
- TensorFlow Skills Practiced: Machine Learning, Deep Learning, Artificial Intelligence
These smart glasses, referred to as Sight, help people who are blind decipher what’s happening around them. It features a camera, button, and Raspberry Pi. Once the user presses the button, an image is taken by the camera. This image is processed through TensorFlow and helps the user learn about it through a voice assistant.
- TensorFlow Skills Practiced: Deep Learning, Artificial Intelligence
This is a silver bit based on TensorFlow that uses mathematical rules to fill out the boxes. It features Raspberry Pi3 and a camera. Once the camera takes an image, it is processed and segmented into different boxes. The neural network analyzes the image and provides a numerical grid.
- TensorFlow Skills Practiced: Machine Learning, Deep Learning
In this project, you will classify customers based on age, gender, history, interest, and other factors using preexisting data. TensorFlow works on producing sound data. It’s an excellent project for business owners looking to delve deeper into their niche, as it functions well for large companies accommodating broad audiences.
- TensorFlow Skills Practiced: Machine Learning, Deep Learning,
This is an intermediate project that utilizes the TensorFlow Object Counting API function. The function helps in detection, tracking, and counting vehicles. To make it more challenging, the project can incorporate the classification of cars, speed, color, and size.
The entire project is based on OpenCV and TensorFlow. OpenCV helps in color detection, speed measurement, and pixel manipulation. Both frameworks can be used in image recognition, but OpenCV is the preferred option.
Advanced TensorFlow Project Ideas
If you are already an expert at utilizing TensorFlow, you can use these advanced project ideas to further expand your skills. These real-world examples require valid experience and expertise to complete successfully.
SkyFall: Gesture Controlled Web-based Game using TensorFlow Object Detection API
- TensorFlow Skills Practiced: Machine Learning, Deep Learning, Natural Language Processing
The physics-based game called Skyfall allows the user to gesture towards the webcam to move the paddles. This is also possible when there are multiple players in the game. The TensorFlow Object Detection API detects the movement of the hand and transmutes it to the game interface using FLASK.
Meter Maid Monitor: parking protection with Pi
- TensorFlow Skills Practiced: Artificial Intelligence, Machine Learning, Deep Learning, Neural Networks
There are cities with minimal parking-time space that may benefit from Meter Maid. This is an AI used to inform the owner of a vehicle that their designated time for parking has elapsed. The entire project is built on TensorFlow, Raspberry Pi, and Amazon Web Services (AWS).
Music Genre Classification
- TensorFlow Skills Practiced: Machine Learning, Deep Learning, APIs
In this project, you will be identifying different sounds and tones using TensorFlow features for extraction, training, and model building. There is also an online deployment that ensures the APIs carry out their functions. To improve precision, the project will rely on multilevel binary classification.
Advanced NLP Projects with TensorFlow 2.0
- TensorFlow Skills Practiced: Deep Learning, Natural Language Processing
In this project, you will find real-world natural language processing (NLP) projects and gain the best insights from your data. The real-world projects specifically focus on the interaction between humans and TensorFlow 2.0. You will also cover Jupyter notebook and textual data sources. By the end, you’ll have hands-on skills to tackle NLP techniques and projects.
Farmaid: Plant Disease Detection Robot
- TensorFlow Skills Practiced: Raspberry Pi
Farmaid is a robot that tends to greenhouse plants and identifies diseases that may affect them. The machine learning robot utilizes object detection techniques to carry out its responsibilities without damaging the plants. This is an excellent project that saves farmers time and labor costs. This project exercises your skills in machine learning and basic image classification.
TensorFlow Starter Project Templates
There is no need to start from scratch when using TensorFlow. You can efficiently utilize the TensorFlow starter project templates to polish your skill set. These project templates feature tools and technologies to help ease the process of building your project.
- Create a TFX pipeline using templates. Through this template, you will learn how to build a TensorFlow Extended pipeline. You will go through the introduction then proceed to a step-by-step guide in setting up the pipeline. You can set up your environment, copy the template, and browse the source files. Complete it by running your TFX pipeline.
- TensorFlow Project Template. You can use this template for Deep Learning projects. The template will help you focus on modeling, training, and configuration. It features a simple and well-designed structure that helps you change the core idea into any new TensorFlow project. You’ll begin with an introduction before proceeding to the template, which features project architecture, folder structure, and main components.
- TensorFlow Template 2. This is another deep learning template to help you change the core of the model each time you start a new project.
- TensorFlow Template. This deep learning template will help you build projects by changing the core elements. In this template, the model, train, and summary are divided into three parts. This simplifies reading the lines of code. The project combines all of them and provides more template code.
- MrGemy95/TensorFlow-Project-Template. This template helps you build your project faster by focusing on core features. You can use Github for automating and streamlining your workflow, and sort tasks by adding issues and pulling requests to your board. You can create a task list to prioritize the workflow set up triggers to notify you when the work should be done.
Next Steps: Start Organizing Your TensorFlow Portfolio
When used correctly, a well-developed professional portfolio can help you land any job involving TensorFlow, machine learning, and artificial intelligence. Below you will find some tips to help you effectively prepare your portfolio for presentation to potential employers.
Highlight Your Achievements
Your portfolio should highlight your ability to solve specific problems through your skills and creativity. Make sure you select your strongest projects and prepare a few key points about each one. Explain why you took on the project, the problem you were trying to tackle, and how you leveraged your different talents.
Make It Relevant
The best way to know what to put in your portfolio is by checking the job description. Make sure you organize your projects according to the needs of the company you are applying for.
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You should also ensure you are citing skills and experience that align with the current demands in the market.
Keep It Simple
A well-curated portfolio is simple and straightforward. You should present a portfolio that reflects the needs of the recruiter. Make sure you highlight key points and don’t get bogged down by the details. Filling your portfolio with unnecessary remarks or projects may cause recruiters to lose interest.
TensorFlow Projects FAQ
TensorFlow is used for building machine learning models, deploying machine learning productions, and research in these fields. The open-source library features extensive tools and resources for real-world scenarios.
TensorFlow was developed by the Google Brain Team and will likely continue to be relevant for a long time. TensorFlow is used by top tech companies, including Google, Twitter, Uber, DropBox, and Airbnb. You will find them utilizing the framework for image recognition, virtual assistance, natural language processing, and recommendation systems.
Yes, there are TensorFlow certifications that can help you validate your skills in this machine learning framework. You’ll need to prepare for and pass the associated exam to receive your certification. This can greatly boost your candidacy across a variety of industries.
Yes, most TensorFlow bootcamps require students to complete TensorFlow capstone projects before graduation. These projects are vital for helping them practice their skills and get recognized by recruiting teams from hiring partners.
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