Pickl AI

AUGUST 14, 2024

History and Evolution of Neural Networks The concept of neural networks dates back to the 1940s, with the introduction of the perceptron by Frank Rosenblatt, which laid the groundwork for supervised learning. Forward Propagation: Input data is passed through the network, and predictions are made.

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Pickl AI

NOVEMBER 18, 2024

Key Takeaways Machine Learning Models are vital for modern technology applications. Types include supervised, unsupervised, and reinforcement learning. Key steps involve problem definition, data preparation, and algorithm selection. Data quality significantly impacts model performance. What’s the goal?

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IBM Journey to AI blog

AUGUST 11, 2023

Because ML is becoming more integrated into daily business operations, data science teams are looking for faster, more efficient ways to manage ML initiatives, increase model accuracy and gain deeper insights. MLOps is the next evolution of data analysis and deep learning. Foundation models aim to solve this problem.

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Mlearning.ai

JUNE 1, 2023

Using PyTorch Deep Learning Framework and CNN Architecture Photo by Andrew S on Unsplash Motivation Build a proof-of-concept for Audio Classification using a deep-learning neural network with PyTorch framework. Data Source here. This is inherently a supervised learning problem.

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Dataconomy

MARCH 27, 2023

The goal is to create algorithms that can make predictions or decisions based on input data, without being explicitly programmed to do so. Unsupervised learning:  This involves using unlabeled data to identify patterns and relationships within the data.

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Mlearning.ai

NOVEMBER 29, 2023

Scientific studies forecasting  — Machine Learning and deep learning for time series forecasting accelerate the rates of polishing up and introducing scientific innovations dramatically. 19 Time Series Forecasting Machine Learning Methods How exactly does time series forecasting machine learning work in practice?

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phData

AUGUST 24, 2023

Now that we have a firm grasp on the underlying business case, we will now define a machine learning pipeline in the context of credit models. Machine learning in credit scoring and decisioning typically involves supervised learning , a type of machine learning where the model learns from labeled data.

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The MLOps Blog

FEBRUARY 22, 2024

Important note: Continual learning aims to allow the model to effectively learn new concepts while ensuring it does not forget already acquired information. Plenty of CL techniques exist that are useful in various machine-learning scenarios. There is no incremental training and no continual learning.

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DagsHub

NOVEMBER 18, 2024

Each of these tools comes up with its unique features and capabilities such as support for automated annotation, handling huge amounts of data, taking care of security requirements, etc. However, the growth of deep learning concepts like transformers , GANs , etc. has enabled the use of image data in large volumes.

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