Optimization Algorithms in Deep Learning
This module talks about optimization algorithms or optimizers in deep learning. An optimization algorithm finds the value of the parameters (weights) that minimize the error when mapping inputs to outputs. Optimization algorithms are search methods, where the goal is to find a solution to an optimization problem, such that a given quantity is optimized, possibly subject to a set of constraints.
Convolutional Neural Networks
A convolutional neural network (CNN) is a type of artificial neural network used primarily for image recognition and processing, due to its ability to recognize patterns in images.
Structuring Machine Learning
Structured machine learning refers to gaining knowledge of established hypotheses from statistics with rich inner structure typically withinside one or greater relations. This course covers ML Strategy, Train, Dev and Dev Tests and Comparing to Human Level Performance.
Natural Language Processing
This covers covers basic Introduction to NLP & How it works' . Natural Language Processing (NLP) is a subfield of Artificial Intelligence that focuses on the interaction between computers and human language. The primary goal of NLP is to enable machines to understand, interpret, and generate human language in a way that is both meaningful and contextually relevant.
It also talks about 'Logical Regression and 'Sentiment Analysis using different algorithms'.