Machine Learning
Showing 121–132 of 233 results
Intro to PyTorch and Neural Networks
Learn how to use PyTorch to build, train, and test artificial neural networks in this course.
Intro to Regularization with Python
Improve machine learning performance with regularization.
Introduction to AI and Machine Learning on Google Cloud
This course introduces the AI and machine learning (ML) offerings on Google Cloud that build both predictive and generative AI projects.
Introduction to Deep Learning in Python
Learn the fundamentals of neural networks and how to build deep learning models using Keras 2.0 in Python.
Introduction to Deep Learning with Keras
Learn to start developing deep learning models with Keras.
Introduction to Linear Modeling in Python
Explore the concepts and applications of linear models with python and build models to describe, predict, and extract insight from data patterns.
Introduction to TensorFlow
This course is focused on using the flexibility and “ease of use” of TensorFlow 2.x and Keras to build, train, and deploy machine learning models. You will learn about the TensorFlow 2.x API hierarchy and will get to know the main components of TensorFlow through hands-on exercises. We will introduce you to working with datasets and feature columns. You will learn how to design and build a TensorFlow 2.x input data pipeline. You will get hands-on practice loading csv data, numPy arrays, text data, and images using tf.Data.Dataset. You will also get hands-on practice creating numeric, categorical, bucketized, and hashed feature columns. We will introduce you to the Keras Sequential API and the Keras Functional API to show you how to create deep learning models. We’ll talk about activation functions, loss, and optimization. Our Jupyter Notebooks hands-on labs offer you the opportunity to build basic linear regression, basic logistic regression, and advanced logistic regression machine learning models. You will learn how to train, deploy, and productionalize machine learning models at scale with Cloud AI Platform.
Introduction to TensorFlow in Python
Learn the fundamentals of neural networks and how to build deep learning models using TensorFlow.
LangChain Techniques for Complex Datasets
Transform the way you work with large-scale data. This course will teach you how to leverage the power of LangChain to efficiently handle, query, and analyze complex datasets.
Language Models in Python: Basic Chatbots
Build rules- and retrieval-based chatbots in Python.
Language Models in Python: Generative Chatbots
Build chatbots in Python using deep learning.
Launching into Machine Learning
The course begins with a discussion about data: how to improve data quality and perform exploratory data analysis. We describe Vertex AI AutoML and how to build, train, and deploy an ML model without writing a single line of code. You will understand the benefits of Big Query ML. We then discuss how to optimize a machine learning (ML) model and how generalization and sampling can help assess the quality of ML models for custom training.