Download and Learn Deep Learning Udacity Nanodegree Course 2022 for free with google drive download link.
Deep learning is driving advances in artificial intelligence that are changing our world. Enroll now to build and apply your own deep neural networks to challenges like image classification and generation, time-series prediction, and model deployment.
In collaboration with
What you will learn in Deep Learning Nanodegree
4 months to complete
Become an expert in neural networks, and learn to implement them using the deep learning framework PyTorch. Build convolutional networks for image recognition, recurrent networks for sequence generation, generative adversarial networks for image generation, and learn how to deploy models accessible from a website.
Deep Learning Nanodegree Intro Video:
This program has been created specifically for students who are interested in machine learning, AI, and/or deep learning, and who have a working knowledge of Python programming, including NumPy and pandas. Outside of that Python expectation and some familiarity with calculus and linear algebra, it’s a beginner-friendly program.
See detailed requirements Below ????
This program has been created specifically for students who are interested in machine learning, AI, and/or deep learning, and who have a basic working knowledge of Python programming. Outside of that Python expectation, it’s a very beginner-friendly program.
Get your first taste of deep learning by applying style transfer to your own images, and gain experience using development tools such as Anaconda and Jupyter notebooks.
Learn neural networks basics, and build your first network with Python and NumPy. Use the modern deep learning framework PyTorch to build multi-layer neural networks, and analyze real data.
Project – Predicting Bike-Sharing Patterns
Build and train neural networks from scratch to predict the number of bikeshare users on a given day.
Convolutional Neural Networks
Learn how to build convolutional networks and use them to classify images (faces, melanomas, etc.) based on patterns and objects that appear in them. Use these networks to learn data compression and image denoising.
Project – Landmark Classification & Tagging for Social Media
In this project, you will apply the skills you have acquired in the course to build a landmark classifier.
Photo-sharing services or photo-storage services may use landmark classification to automatically tag photos with relevant hashtags or location markers. This type of functionality could be especially important when photo location metadata is not available, which could happen when a photo is taken without metadata (e.g., phone was on airplane mode, camera was old and without GPS) or if a photo has had its metadata scrubbed.
In the project, you will go through a machine learning design process end-to-end: performing data preprocessing and augmentation, designing your own CNN from scratch, and training and saving your best CNN model. You will also use transfer learning and compare your transfer-learned model with your from-scratch CNN.
Recurrent Neural Networks
Build your own recurrent networks and long short-term memory networks with PyTorch; perform sentiment analysis and use recurrent networks to generate new text from TV scripts.
Project – Generate TV scripts
Build a recurrent neural network on TensorFlow to process text. Use it to generate new episodes of your favorite TV show, based on old scripts.
Generative Adversarial Networks
Learn to understand and implement a Deep Convolutional GAN (generative adversarial network) to generate realistic images, with Ian Goodfellow, the inventor of GANs, and Jun-Yan Zhu, the creator of CycleGANs.
Project – Generate Faces
Build a pair of multi-layer neural networks and make them compete against each other in order to generate new, realistic faces. Try training them on a set of celebrity faces, and see what new faces the computer comes out with!
Deploying a Sentiment Analysis Model
Train and deploy your own PyTorch sentiment analysis model. Deployment gives you the ability to use a trained model to analyze new, user input. Build a model, deploy it, and create a gateway for accessing it from a website.
Project – Deploying a Sentiment Analysis Model
Train and deploy your own PyTorch sentiment analysis model. You’ll build a model and create a gateway for accessing it from a website.
Need to prepare? You’ll need intermediate experience with Python to start this program. Some basic knowledge of machine learning is beneficial, although not required, to start this program. Prepare now with AI Programming with Python.
The share of jobs requiring AI skills has grown 4.5x since 2013
All our programs include:
Real-world projects from industry experts
With real world projects and immersive content built in partnership with top tier companies, you’ll master the tech skills companies want.
Technical mentor support
Our knowledgeable mentors guide your learning and are focused on answering your questions, motivating you and keeping you on track.
You’ll have access to Github portfolio review and LinkedIn profile optimization to help you advance your career and land a high-paying role.
Flexible learning program
Tailor a learning plan that fits your busy life. Learn at your own pace and reach your personal goals on the schedule that works best for you.
Regarding Google Drive, we are only accepting 100 file requests per day because Google has banned our Drive account from publicly sharing larger files. Additionally, some websites are using our files without giving us credit. So we’ve made the course material / file private; you can request it, but it’s first come, first served. We are currently receiving over 6000+ file requests per day.
Now we have all updated Udacity Courses up to June 8, 2022 – new courses, totaling 78 Nanodegree Courses with full Materials (Note: We are the only website on the internet to have all the Updated Udacity Course).
Use This Password to Extract file: “udacitycourses.com“
We have Shared Mediafire / Mega.nz download link for Some Courses updated on 2019 in our Telegram Channel and More info about Dedicated Drive and for Support: