01-21-2023, 02:35 PM
Complete Data Science BootCamp
Learn about Data Science, Machine Learning and Deep Learning and build 5 different projects.
New
Rating: 0.0 out of 5
(0 ratings)
1,149 students
7.5 hours on-demand video
61 downloadable resources
Description
Data science is the field that encompasses the various techniques and methods used to extract insights and knowledge from data. Machine learning (ML) and deep learning (DL) are both subsets of data science, and they are often used together to analyze and understand data.
In data science, ML algorithms are often used to build predictive models that can make predictions based on historical data. These models can be used for tasks such as classification, regression, and clustering. ML algorithms include linear regression, decision trees, and k-means.
DL, on the other hand, is a subset of ML that is based on artificial neural networks with multiple layers, which allows the system to learn and improve through experience. DL is particularly well-suited for tasks such as image recognition, speech recognition, and natural language processing. DL algorithms include convolutional neural networks (CNNs) and recurrent neural networks (RNNs).
https://www.udemy.com/course/complete-data-science-bootcamp/?couponCode=B04843ABD9AEF7573FEC
Enjoy!
Learn about Data Science, Machine Learning and Deep Learning and build 5 different projects.
New
Rating: 0.0 out of 5
(0 ratings)
1,149 students
7.5 hours on-demand video
61 downloadable resources
Description
Data science is the field that encompasses the various techniques and methods used to extract insights and knowledge from data. Machine learning (ML) and deep learning (DL) are both subsets of data science, and they are often used together to analyze and understand data.
In data science, ML algorithms are often used to build predictive models that can make predictions based on historical data. These models can be used for tasks such as classification, regression, and clustering. ML algorithms include linear regression, decision trees, and k-means.
DL, on the other hand, is a subset of ML that is based on artificial neural networks with multiple layers, which allows the system to learn and improve through experience. DL is particularly well-suited for tasks such as image recognition, speech recognition, and natural language processing. DL algorithms include convolutional neural networks (CNNs) and recurrent neural networks (RNNs).
https://www.udemy.com/course/complete-data-science-bootcamp/?couponCode=B04843ABD9AEF7573FEC
Enjoy!