Towards AI

AUGUST 25, 2023

Machine learning (ML) is a subset of AI that provides computer systems the ability to automatically learn and improve from experience without being explicitly programmed. Deep learning (DL) is a subset of machine learning that uses neural networks which have a structure similar to the human neural system.

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Machine Learning Machine Learning AI AI 98

Mlearning.ai

JUNE 6, 2023

In today’s blog, we will see some very interesting Python Machine Learning projects with source code. This list will consist of Machine learning projects, Deep Learning Projects, Computer Vision Projects , and all other types of interesting projects with source codes also provided.

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Mlearning.ai

JUNE 7, 2023

This is one of the best Machine learning projects in Python. Doctor-Patient Appointment System in Python using Flask Hey guys, in this blog we will see a Doctor-Patient Appointment System for Hospitals built in Python using Flask. We have the IPL data from 2008 to 2017. Working Video of our App [link] 7.

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Machine Learning Machine Learning Python Deep Learning 52

Mlearning.ai

MAY 23, 2023

This is one of the best Machine Learning Projects for final year in Python. In this article, we will discuss the development of a Leaf Disease Detection Flask App that uses a deep learning model to automatically detect the presence of leaf diseases. We have the IPL data from 2008 to 2017.

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Mlearning.ai

MAY 21, 2023

Here, we will discuss some popular machine learning projects with source code that you can explore: 1. Youtube Comments Extraction and Sentiment Analysis Flask App Hey, guys in this blog we will implement Youtube Comments Extraction and Sentiment Analysis in Python using Flask. We have the IPL data from 2008 to 2017.

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AWS Machine Learning Blog

SEPTEMBER 23, 2024

This dataset contains 10 years (1999–2008) of clinical care data at 130 US hospitals and integrated delivery networks. For instance, instead of a vague query about AWS services, try: “Can you provide sample code using the SageMaker Python SDK library to train an XGBoost model in SageMaker?” Let’s start with data exploration.

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AWS Machine Learning Blog

SEPTEMBER 11, 2024

In terms of resulting speedups, the approximate order is programming hardware, then programming against PBA APIs, then programming in an unmanaged language such as C++, then a managed language such as Python. Together, these elements lead to the start of a period of dramatic progress in ML, with NN being redubbed deep learning.

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