Towards AI

AUGUST 16, 2023

We can apply a data-centric approach by using AutoML or coding a custom test harness to evaluate many algorithms (say 20–30) on the dataset and then choose the top performers (perhaps top 3) for further study, being sure to give preference to simpler algorithms (Occam’s Razor).

AI 98

AI AI Machine Learning Machine Learning 98

Pickl AI

JANUARY 3, 2024

Feature engineering in machine learning is a pivotal process that transforms raw data into a format comprehensible to algorithms. EDA, imputation, encoding, scaling, extraction, outlier handling, and cross-validation ensure robust models. What is Feature Engineering? Steps of Feature Engineering 1.

Machine Learning 52

Machine Learning Machine Learning Exploratory Data Analysis Cross Validation 52

Pickl AI

FEBRUARY 12, 2024

Technical Proficiency Data Science interviews typically evaluate candidates on a myriad of technical skills spanning programming languages, statistical analysis, Machine Learning algorithms, and data manipulation techniques. Differentiate between supervised and unsupervised learning algorithms. Here is a brief description of the same.

Data Science 52

Data Science Cross Validation Machine Learning Machine Learning 52

Pickl AI

JULY 12, 2024

Their interactive nature makes them suitable for experimenting with AI algorithms and analysing data. Machine Learning algorithms are trained on large amounts of data, and they can then use that data to make predictions or decisions about new data.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Python Natural Language Processing 52

DrivenData Labs

APRIL 10, 2024

In the Kelp Wanted challenge, participants were called upon to develop algorithms to help map and monitor kelp forests. Winning algorithms will not only advance scientific understanding, but also equip kelp forest managers and policymakers with vital tools to safeguard these vulnerable and vital ecosystems.

Deep Learning 130

Deep Learning Deep Learning Machine Learning Machine Learning 130

Mlearning.ai

NOVEMBER 23, 2023

This simplifies the process of model selection and evaluation, making it easier than ever to choose the right algorithm for your supervised learning task. You may need to import more libraries for EDA, preprocessing, and so on depending on the dataset you’re dealing with. STEP 1: Install the lazypredict library.

Supervised Learning 52

Supervised Learning Cross Validation EDA Machine Learning 52

Pickl AI

DECEMBER 16, 2024

Summary: AI in Time Series Forecasting revolutionizes predictive analytics by leveraging advanced algorithms to identify patterns and trends in temporal data. Advanced algorithms recognize patterns in temporal data effectively. Key Takeaways AI automates complex forecasting processes for improved efficiency.

AI 52

AI AI Machine Learning Machine Learning 52