Dataconomy

JUNE 29, 2023

Python machine learning packages have emerged as the go-to choice for implementing and working with machine learning algorithms. These libraries, with their rich functionalities and comprehensive toolsets, have become the backbone of data science and machine learning practices. Why do you need Python machine learning packages?

Machine Learning 113

Machine Learning Machine Learning Deep Learning Deep Learning 113

Pickl AI

JULY 12, 2024

Summary: This guide explores Artificial Intelligence Using Python, from essential libraries like NumPy and Pandas to advanced techniques in machine learning and deep learning. Python’s simplicity, versatility, and extensive library support make it the go-to language for AI development.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Python Natural Language Processing 52

Mlearning.ai

MARCH 15, 2023

Build a Stocks Price Prediction App powered by Snowflake, AWS, Python and Streamlit — Part 2 of 3 A comprehensive guide to develop machine learning applications from start to finish. Introduction Welcome Back, Let's continue with our Data Science journey to create the Stock Price Prediction web application.

Python 52

Python AWS Exploratory Data Analysis Machine Learning 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. What is cross-validation, and why is it used in Machine Learning?

Data Science 52

Data Science Cross Validation Machine Learning Machine Learning 52

Ocean Protocol

FEBRUARY 1, 2024

This is a unique opportunity for data people to dive into real-world data and uncover insights that could shape the future of aviation safety, understanding, airline efficiency, and pilots driving planes. When implementing these models, you’ll typically start by preprocessing your time series data (e.g.,

Exploratory Data Analysis 52

Exploratory Data Analysis Data Science Cross Validation Machine Learning 52

Pickl AI

FEBRUARY 22, 2024

The dedicated Statistics module focussing on Exploratory Data Analysis, Probability Theory, and Inferential Statistics. Statistical Fundamentals with R DataCamp 20 hours Introducing students to Statistical concepts Data Scientists use, this course covers correlation, regression, exploratory Data Analysis, and inference.

Data Science 52

Data Science Hypothesis Testing Data Analysis Data Analysis 52

Pickl AI

MARCH 26, 2024

Experimentation and cross-validation help determine the dataset’s optimal ‘K’ value. Distance Metrics Distance metrics measure the similarity between data points in a dataset. Implementing the KNN algorithm involves several steps, from preprocessing the data to training the model and making predictions.

K-nearest Neighbors 52

K-nearest Neighbors Machine Learning Machine Learning Algorithm 52