Search result for Courses taught by Joseph Santarcangelo
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Python Basics for Data Science
by Joseph Santarcangelo- 0.0
5 Weeks
This Python course provides a beginner-friendly introduction to Python for Data Science. Practice through lab exercises, and you'll be ready to create your first Python scripts on your own! Kickstart your learning of Python for data science, as well as programming in general with this introduction to Python course. ~~~~ In this course you will learn about:...
$99
Analyzing Data with Python
by Joseph Santarcangelo- 0.0
5 Weeks
In this course, you will learn how to analyze data in Python using multi-dimensional arrays in numpy, manipulate DataFrames in pandas, use SciPy library of mathematical routines, and perform machine learning using scikit-learn! LEARN TO ANALYZE DATA WITH PYTHON Learn how to analyze data using Python in this introductory course. You will learn how to: __...
$99
¡Conceptos básicos de Python para Data Science!
by Joseph Santarcangelo- 0.0
5 Weeks
Este curso de Python proporciona una introducción para principiantes a Python a la ciencia de datos. Practica a través de ejercicios de laboratorio, ¡y estarás listo para crear tus primeros scripts de Python por tu cuenta! Comienza tu aprendizaje de Python para la ciencia de datos, así como programación en general con esta introducción a Python....
$49
Deep Learning with Python and PyTorch
by Joseph Santarcangelo- 0.0
6 Weeks
This course is the second part of a two-part course on how to develop Deep Learning models using Pytorch. NOTE: In order to be successful in completing this course, please ensure you are familiar with PyTorch Basics and have practical knowledge to apply it to Machine Learning. You will finally learn about dimensionality reduction and autoencoders....
$99
PyTorch Basics for Machine Learning
by Joseph Santarcangelo- 0.0
5 Weeks
This course is the first part in a two part course and will teach you the fundamentals of PyTorch. In this course you will implement classic machine learning algorithms, focusing on how PyTorch creates and optimizes models. This is followed by an in-depth overview of the dataset object and transformations; this is the first step in building Pipelines in PyTorch....
$39
Analizando datos con Python
by Joseph Santarcangelo- 0.0
5 Weeks
En este curso aprenderás cómo analizar datos en Python usando matrices multidimensionales en numpy, a manipular DataFrames en pandas, a usar la biblioteca SciPy de rutinas matemáticas y a realizar aprendizaje automático usando scikit-learn. APRENDE A ANALIZAR DATOS CON PYTHON Aprende a analizar datos usando Python en este curso introductorio. ●...
$39
Applied Deep Learning Capstone Project
by Joseph Santarcangelo- 0.0
5 Weeks
In this capstone project, you'll use either Keras or PyTorch to develop, train, and test a Deep Learning model. Load and preprocess data for a real problem, build the model and then validate it. In this capstone project, you'lluse a Deep Learning library ofyour choice to develop, train, and test a Deep Learning model....
$149
Data Analysis with Python
by Joseph Santarcangelo- 4.7
Approx. 13 hours to complete
Learn how to analyze data using Python. This course will take you from the basics of Python to exploring many different types of data. You will learn how to prepare data for analysis, perform simple statistical analysis, create meaningful data visualizations, predict future trends from data, and more! Topics covered: 1) Importing Datasets...
Machine Learning with Python
by SAEED AGHABOZORGI , Joseph Santarcangelo- 4.7
Approx. 21 hours to complete
This course dives into the basics of machine learning using an approachable, and well-known programming language, Python. In this course, we will be reviewing two main components: First, you will be learning about the purpose of Machine Learning and where it applies to the real world. Introduction to Machine Learning Welcome...
Deep Neural Networks with PyTorch
by Joseph Santarcangelo- 4.4
Approx. 31 hours to complete
The course will teach you how to develop deep learning models using Pytorch. The course will start with Pytorch's tensors and Automatic differentiation package. Then each section will cover different models starting off with fundamentals such as Linear Regression, and logistic/softmax regression. Followed by Feedforward deep neural networks, the role of different activation functions, normalization and dropout layers....