Data Science Blog

FEBRUARY 23, 2023

1, Data is the new oil, but labeled data might be closer to it Even though we have been in the 3rd AI boom and machine learning is showing concrete effectiveness at a commercial level, after the first two AI booms we are facing a problem: lack of labeled data or data themselves. That is, is giving supervision to adjust via.

Supervised Learning 264

Supervised Learning Machine Learning Machine Learning Deep Learning 264

Pickl AI

NOVEMBER 4, 2024

Scikit-learn Scikit-learn is the go-to library for Machine Learning in Python. Scikit-learn covers various classification , regression , clustering , and dimensionality reduction algorithms. Perform exploratory Data Analysis (EDA) using Pandas and visualise your findings with Matplotlib or Seaborn.

Data Science 52

Data Science Python Machine Learning Machine Learning 52

Pickl AI

JULY 12, 2024

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. There are three main types of Machine Learning: supervised learning, unsupervised learning, and reinforcement learning.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Python Natural Language Processing 52

Pickl AI

FEBRUARY 12, 2024

Differentiate between supervised and unsupervised learning algorithms. Supervised learning algorithms learn from labelled data, where each input is associated with a corresponding output label. Clustering algorithms such as K-means and hierarchical clustering are examples of unsupervised learning techniques.

Data Science 52

Data Science Cross Validation Machine Learning Machine Learning 52

Becoming Human

MAY 15, 2023

For Data Analysis you can focus on such topics as Feature Engineering , Data Wrangling , and EDA which is also known as Exploratory Data Analysis. First learn the basics of Feature Engineering, and EDA then take some different-different data sheets (data frames) and apply all the techniques you have learned to date.

Data Science 75

Data Science Machine Learning Machine Learning Database 75

Pickl AI

SEPTEMBER 12, 2024

Boosting: An ensemble learning technique that combines multiple weak models to create a strong predictive model. C Classification: A supervised Machine Learning task that assigns data points to predefined categories or classes based on their characteristics.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52