Flipboard

JUNE 13, 2025

To excel in ML, you must understand its key methodologies: Supervised Learning: Involves training models on labeled datasets for tasks like classification (e.g., Reinforcement Learning: Teaches agents to make decisions by interacting with their environment, commonly applied in robotics, gaming, and autonomous systems.

Artificial Intelligence 68

Artificial Intelligence Artificial Intelligence Exploratory Data Analysis Machine Learning 68

Pickl AI

NOVEMBER 4, 2024

Here are some recommended projects to help reinforce your learning: Data Analysis Project Start with a dataset from sources like Kaggle or UCI Machine Learning Repository. 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

Mlearning.ai

NOVEMBER 23, 2023

This Only Applies to Supervised Learning Introduction If you’re like me then you probably like a more intuitive way of doing things. When it comes to machine learning, we often have that one (or two or three) “go-to” model(s) that we tend to rely on for most problems. With Lazypredict. STEP 1: Install the lazypredict library.

Supervised Learning 52

Supervised Learning Cross Validation EDA 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

JULY 12, 2024

Here are a few of the key concepts that you should know: Machine Learning (ML) This is a type of AI that allows computers to learn without being explicitly programmed. 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

ODSC - Open Data Science

AUGUST 9, 2023

Our focus will be hands-on, with an emphasis on the practical application and understanding of essential machine learning concepts. Attendees will be introduced to a variety of machine learning algorithms, placing a spotlight on logistic regression, a potent supervised learning technique for solving binary classification problems.

Machine Learning 52

Machine Learning Machine Learning AWS Big Data 52