Download and Learn Intro to Machine Learning with TensorFlow Udacity Nanodegree Course 2023 for free with google drive download link.
Learn foundational machine learning techniques – from data manipulation to unsupervised and supervised algorithms.
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What You’ll Learn in Intro to Machine Learning with TensorFlow Nanodegree
Intro to Machine Learning with TensorFlow
Learn foundational machine learning algorithms, starting with data cleaning and supervised models. Then, move on to exploring deep and unsupervised learning. At each step, get practical experience by applying your skills to code exercises and projects.
This program is intended for students with experience in Python, who have not yet studied Machine Learning topics.
Learn foundational machine learning techniques — from data manipulation to unsupervised and supervised algorithms in TensorFlow and scikit-learn.
3 months to complete
Intro to Machine Learning with TensorFlow Intro Video:
To optimize your chances of success in this program, we recommend intermediate Python programming knowledge and basic knowledge of probability and statistics.
In this lesson, you will learn about supervised learning, a common class of methods for model construction.
Project – Find Donors for CharityML
CharityML is a fictitious charity organization located in the heart of Silicon Valley that was established to provide financial support for people eager to learn machine learning. Your goal will be to evaluate and optimize several different supervised learners to determine which algorithm will provide the highest donation yield while also reducing the total number of letters being sent to ask for donations.
In this lesson, you will learn the foundations of
neural network design and training in TensorFlow.
Project – Create Your Own Image Classifier
As a machine learning engineer at a fictional self-driving car startup, you have been asked to help decide whether to build or buy an object detection algorithm for objects that may be on the side of the road. A company, Detectocorp, claims an 80% accuracy rate on the CIFAR-10 dataset, a benchmark used to evaluate the state of the art for computer vision systems.
You will try your hand at training a neural network to recognize objects in images and evaluate the model’s performance compared to Detectocorp’s model.
In this lesson, you will learn to implement unsupervised learning methods for different kinds of problem domains.
Project – Create Customer Segments
Use unsupervised learning techniques to see if any similarities exist between customers and use those similarities to segment customers into distinct categories using various clustering techniques. This segmentation is used to help the business make more informed marketing and product decisions.
Need to prepare?
LinkedIn ranked AI Specialist as the #1 Emerging Job in 2020, with 74% annual job growth.
Intro to Machine Learning with TensorFlow Nanodegree Free Download Link: