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Logistic Regression from Scratch

Lets us try to implement logistic regression from scratch in python. Recommended to be read after the Neural Networks release. Importing necessary libraries The dataset we will be using is Pima-Indians-diabetes-database Whose objective is to predict whether or not a patient has diabetes diagnostically. y = data.Outcome.values x_data = data.drop([“Outcome”],axis=1)   After this, the data…

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AI

What is simulated annealing in artificial intelligence?

Are you curious about how artificial intelligence algorithms can be used to solve complex problems? Look no further than simulated annealing! This powerful optimization technique is inspired by the physical process of heating and cooling metals and has been adapted for use in AI systems. In this blog post, we’ll dive into what simulated annealing…

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Machine learning

What is neural network in machine learning?

Neural networks are the brainchild of artificial intelligence (AI). They are a type of machine learning that can be used to make predictions based on data. In other words, they can learn and understand complex patterns in data without being explicitly programmed. This makes them incredibly useful for tasks such as image recognition, speech recognition,…

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Neural Network

Implement Neural Networks with Python

This release will deal with the implementation of the neural network using Tensorflow. Using the Titanic Dataset from kaggle Notebook to check and run code: https://www.kaggle.com/code/tanavbajaj/neural-network-basic/notebook Let’s start by importing the libraries import numpy as np import pandas as pd import tensorflow as tf Read the Data data= pd.read_csv(‘../input/titanic/train.csv’)   Select the required data frames…

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