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Bayesian Approach(Geometric Brownian Motion) in Stock Price Simulation
Hyper parameter tuning is an intrinsic part of the ML development cycle. Let's see 2 Bayesian optimization techniques bayes_opt & hyperopt
Matthew 18 May, 2021
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Seismic Analysis with Python
This article in on Seismic Analysis. We will study the relationship between worldwide earthquake distributions and tectonic plate boundaries
Pritam 24 Oct, 2024
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Progressive Growing GAN- ProGAN
ProGAN is an extension of the training process of GAN that allows the generator models to train with stability in python
Syed Abdul Gaffar 16 May, 2021
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Image Processing Using Numpy: With Practical Implementation And Code
Image processing with NumPy! Explore practical implementations and hands-on code to enhance your image manipulation techniques in Python.
Akshay 28 Sep, 2024
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A comprehensive tutorial on Deep Learning – Part 1
Explore deep learning fundamentals, its applications, data requirements, and key concepts like logistic regression and gradient descent.
Sion 30 Jan, 2025
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AIML – A Language for Chatbots
AIML aka Artificial intelligence markup language contains a collection of rules which define the conversational capabilities of the chatbot.
Mayank 18 May, 2021
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StyleGAN Explained in Less Than Five Minutes
The StyleGAN is a continuation of the progressive, developing GAN that is a proposition for training generator models effoetlessly
Mrinal Singh 03 Apr, 2025
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Is there any need of Deep Learning?
Deep learning plays an immense role in data science. In this article we are going to discuss - Is there really any need for deep learning?
Ronil 11 May, 2021
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Making Sense of Astronomical Valuation of Tesla
Let's analyse the valuation of Tesla with respect to other companies in semiconductor, technology and health using python.
sherath 10 May, 2021
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Create a Dummy Stock Market Using Geometric Brownian Motion in Python
Create a replica of a financial stock market or this can be extended to the cryptocurrency market also using Geometric Brownian Motion
Arnab M 28 Oct, 2024
