Pickl AI

APRIL 26, 2024

Overfitting occurs when a model learns the training data too well, including noise and irrelevant patterns, leading to poor performance on unseen data. Techniques such as cross-validation, regularisation , and feature selection can prevent overfitting. How do you handle large datasets in Python?

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52

Mlearning.ai

FEBRUARY 15, 2024

There are many algorithms which can be used from this task ranging from Logistic regression to Deep learning. This cross-validation results shows without regularization. Since our target variable has two classes, we are working with a Binary Classification problem. So we will use accuracy to optimize our hyperparameters.

Data Science 52

Data Science Decision Trees Exploratory Data Analysis Cross Validation 52

Mlearning.ai

MAY 23, 2023

What is deep learning? What is the difference between deep learning and machine learning? Deep learning is a paradigm of machine learning. In deep learning, multiple layers of processing are involved in order to extract high features from the data. What is a computational graph?

Data Science 52

Data Science Decision Trees Deep Learning Deep Learning 52

Data Science Dojo

AUGUST 24, 2023

MLOps practices include cross-validation, training pipeline management, and continuous integration to automatically test and validate model updates. Examples include: Cross-validation techniques for better model evaluation. Managing training pipelines and workflows for a more efficient and streamlined process.

Machine Learning 195

Machine Learning Machine Learning ML ML 195

Heartbeat

FEBRUARY 20, 2023

They are: A Comet ML account A suitable IDE, e.g., VSCode or Jupyter Notebook which can also run in VSCode The latest versions of Scikit-learn, CometML, Pandas, NumPy, joblib, and XGboost libraries A python 3.9+ Additionally, I will use StratifiedKFold cross-validation to perform multiple train-test splits.

Cross Validation 87

Cross Validation ML ML Machine Learning 87

Mlearning.ai

FEBRUARY 10, 2023

For example, if you are using regularization such as L2 regularization or dropout with your deep learning model that performs well on your hold-out-cross-validation set, then increasing the model size won’t hurt performance, it will stay the same or improve. The only drawback of using a bigger model is computational cost.

Machine Learning 52

Machine Learning Machine Learning Deep Learning Deep Learning 52

DagsHub

APRIL 21, 2024

Moving the machine learning models to production is tough, especially the larger deep learning models as it involves a lot of processes starting from data ingestion to deployment and monitoring. It provides different features for building as well as deploying various deep learning-based solutions. What is MLOps?

Machine Learning 59

Machine Learning Machine Learning ML ML 59

Mlearning.ai

FEBRUARY 23, 2023

Perceptron Implementation in Python: Understanding the Basics of Artificial Neural Networks Photo by Jeremy Perkins on Unsplash Perceptron is the most basic unit of an artificial neural network. Python Let’s code a perceptron in Python. It takes several inputs and outputs a single binary decision. A Perceptron.

Python 52

Python Cross Validation Machine Learning Machine Learning 52

Heartbeat

DECEMBER 19, 2023

With the advent of Deep Learning, recommender systems have seen significant advancements. Integration of Comet: Unleashing the Power of Experiment Management and Performance Tracking We need to install and set Comet up to get started with the library in our Python environment. We pay our contributors, and we don't sell ads.

Deep Learning 52

Deep Learning Deep Learning Algorithm Cross Validation 52

PyImageSearch

JANUARY 23, 2023

In this tutorial, you will learn the magic behind the critically acclaimed algorithm: XGBoost. Do you think learning computer vision and deep learning has to be time-consuming, overwhelming, and complicated? Here you’ll learn how to successfully and confidently apply computer vision to your work, research, and projects.

Deep Learning 107

Deep Learning Deep Learning Algorithm Decision Trees 107

Mlearning.ai

FEBRUARY 2, 2023

Normalized age distribution in training and test set [3] The model was implemented in Python and stored in a public GitHub repository (containing source code and the trained models). The use of Jupyter Notebooks was done in order to make it possible to train and validate the models on Google Colab in order to get access to free GPUs.

Cross Validation 52

Cross Validation Deep Learning Deep Learning Artificial Intelligence 52

Heartbeat

MAY 29, 2023

Hyperparameters are the configuration variables of a machine learning algorithm that are set prior to training, such as learning rate, number of hidden layers, number of neurons per layer, regularization parameter, and batch size, among others.

Machine Learning 78

Machine Learning Machine Learning Natural Language Processing Data Preparation 78