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Convolutional Layers in TensorFlow

Last Updated: 12 February 2025

Convolutional layers are the foundation of Convolutional Neural Networks (CNNs), which excel at processing spatial data such as images, time-series data, and volumetric da...read more

AI-ML-DS With Python

What is Low Rank Adaptation (LoRA)?

Last Updated: 13 February 2025

Low-Rank Adaptation (LoRA) is a parameter-efficient fine-tuning technique designed to adapt large pre-trained models for specific tasks without significantly increasing co...read more

What is Fine-Tuning?

Last Updated: 20 May 2025

Fine-tuning allows a pre-trained model to adapt to a new task. This approach uses the knowledge gained from training a model on a large dataset and applying it to a smalle...read more

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What is Layer Normalization?

Last Updated: 01 May 2025

Layer Normalization stabilizes and accelerates the training process in deep learning. In typical neural networks, activations of each layer can vary drastically which lead...read more

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AI-ML-DS With Python

Tanh Activation in Neural Network

Last Updated: 14 February 2025

Tanh (hyperbolic tangent) is a type of activation function that transforms its input into a value between -1 and 1. It is mathematically defined as:f(x) = \tanh(x) = \frac...read more

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Softplus Function in Neural Network

Last Updated: 14 February 2025

Softplus function is a smooth approximation of the ReLU function, defined mathematically as:f(x) = \ln(1 + e^x)Where:x is the input to the function.ln is the natural logar...read more

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Transformer for time series forecasting

Last Updated: 02 June 2025

Transformer are a class of deep learning models that use self-attention mechanisms to learn temporal dependencies and patterns in sequential data. Transformers can predict...read more

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Machine Learning

Time Series Embedding

Last Updated: 30 May 2025

Time series embeddings are the numerical representations of time ordered data sequences which are designed to capture essential patterns in a lower dimensional format. The...read more

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Machine Learning

AI-ML-DS With Python

Time Series Classification

Last Updated: 31 May 2025

Time Series data is the type of data that is recorded over specific time intervals. Any dataset that stores a separate timestamp, whether date or time, can be considered a...read more

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AI-ML-DS With Python

Defensive distillation

Last Updated: 05 June 2025

Defensive distillation is a technique aimed at improving the robustness of deep neural networks against adversarial attacks. It involves training a more robust network by ...read more

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AI-ML-DS With Python

Elu Activation Function in Neural Network

Last Updated: 07 June 2025

ELU is a activation function used in neural networks which is an advanced version of widely used relu activation function. But before understanding ELU it's important to r...read more

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Softmax vs Sigmoid Activation function

Last Updated: 04 June 2025

SoftmaxandSigmoidare both activation functions commonly used in neural networks, but they serve different purposes and are best suited for specific types of classification...read more

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How to use LLMs for Regression

Last Updated: 06 June 2025

LLMs, while originally designed for text-based tasks, can be fine-tuned or prompted for regression by treating the numeric prediction as a language generation problem. Reg...read more

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Natural-language-processing

SELU Activation Function in Neural Network

Last Updated: 07 June 2025

SELU (Scaled Exponential Linear Unit) is an activation function designed to help neural networks train more effectively by keeping the output of each layer automatically n...read more

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Deep Learning for Finance: A comprehensive guide

Last Updated: 06 June 2025

Deep learning is transforming the financial industry by enabling institutions to analyze massive, complex datasets, predict market trends, and manage risk with remarkable ...read more

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AI-ML-DS With Python

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