What you would learn in  Machine Learning and Deep Learning Bootcamp in Python course?
Regression-related problems can be solved (linear regression as well as logistic regression)
Resolving problems with classification (naive Bayes classifier, Support Vector Machines SVMs)
Using neural networks (feedforward neural networks, deep neural networks, convolutional neural networks, and recurrent neural networks
The most current machine learning techniques employed by companies like Google or Facebook
Face detection using OpenCV
TensorFlow and Keras
Deep learning - deep neural networks, convolutional neural networks (CNN), recurrent neural networks (RNNs)
Reinforcement learning, Q learning, and deep Q-learning approaches
Basic Python Then we'll employ Panda and Numpy, too (we will go over the basics in implementations)
This class will cover the fundamentals of machine learning. The course will concentrate specifically on the concepts of regression SVM neural networks, decision trees, and SVM. These subjects are becoming popular because the algorithms for learning can be utilized in many fields, including software engineering and investment banking. Learning algorithms can detect patterns that help detect cancer, for instance. Alternatively, we might develop algorithms that make a pretty accurate prediction of the direction of price movements on the market.
In each section, we will discuss the theoretical basis for these algorithms and then solve these problems in conjunction. We will be using Python together with SkLearn, Keras, and TensorFlow.
Machine Learning Algorithms Machine learning methods are becoming increasingly relevant even into 2020. Through this class, you will discover:
linear regression model
logistic regression model
K nearest neighbor classifier
Naive Bayes classifier
support vector machines (SVMs)
Random forest classifier
principal components analysis (PCA)
Machine Learning techniques are used in finance using learning algorithms to predict the price of stocks
Computer Vision as well as Face detection using OpenCV
Neural Networks What are feedforward neural networks, and how do they work?
Deep Learning: neural networks that feedforward and deep neural networks represent modern techniques for artificial intelligence by 2020. What are the subjects you'll learn about in this class?
deep neural networks
convolutional neural networks (CNNs)
recurrent neural networks (RNNs)
Recurrent Neural Networks and Convolutional Neural Networks and their applications, such as sentiment analysis or stock price forecast
reinforcement learning: Markov Decision processes (MDPs) and Q-learning
Tic Tac Toe game with a Q-learning approach and more profound Q-learning method
Who is this course intended for:
This course is intended for those who aren't experienced with deep learning, machine computing, computers, or reinforcement learning, or for students needing a quick refresher
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