Pickl AI

JANUARY 29, 2024

Summary: In the tech landscape of 2024, the distinctions between Data Science and Machine Learning are pivotal. Data Science extracts insights, while Machine Learning focuses on self-learning algorithms. ML catalyses AI advancements, enabling systems to evolve and improve decision-making.

Data Science 52

Data Science ML ML Machine Learning 52

Pickl AI

SEPTEMBER 12, 2024

Summary : This article equips Data Analysts with a solid foundation of key Data Science terms, from A to Z. Introduction In the rapidly evolving field of Data Science, understanding key terminology is crucial for Data Analysts to communicate effectively, collaborate effectively, and drive data-driven projects.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52

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. Introduction Artificial Intelligence (AI) transforms industries by enabling machines to mimic human intelligence.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Python Natural Language Processing 52

Mlearning.ai

FEBRUARY 15, 2024

Data Science Project — Predictive Modeling on Biological Data Part III — A step-by-step guide on how to design a ML modeling pipeline with scikit-learn Functions. Photo by Unsplash Earlier we saw how to collect the data and how to perform exploratory data analysis. Now comes the exciting part ….

Data Science 52

Data Science Decision Trees Exploratory Data Analysis ML 52

Pickl AI

MAY 30, 2024

You will collect and clean data from multiple sources, ensuring it is suitable for analysis. You will perform Exploratory Data Analysis to uncover patterns and insights hidden within the data. Data Integration Data integration combines data from different sources into a single dataset.

Data Analysis 52

Data Analysis Data Analysis Data Science Exploratory Data Analysis 52

Pickl AI

APRIL 26, 2024

This comprehensive blog outlines vital aspects of Data Analyst interviews, offering insights into technical, behavioural, and industry-specific questions. It covers essential topics such as SQL queries, data visualization, statistical analysis, machine learning concepts, and data manipulation techniques.

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52

Pickl AI

FEBRUARY 12, 2024

Data Science skills that will help you excel professionally. 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.

Data Science 52

Data Science Cross Validation Machine Learning Machine Learning 52

Pickl AI

JULY 10, 2023

R is a popular programming language and environment widely used in the field of data science. It provides a comprehensive suite of tools, libraries, and packages specifically designed for statistical analysis, data manipulation, visualization, and machine learning.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Heartbeat

SEPTEMBER 28, 2023

Hands-on Project Why customer churn matters and how to predict it with machine learning, explained step-by-step Photo by Gabrielle Ribeiro on Unsplash Introduction In today’s competitive business environment, retaining customers is essential to a company’s success. Follow “Nhi Yen” for future updates! Our project uses Comet ML to: 1.

Machine Learning 52

Machine Learning Machine Learning Support Vector Machines ML 52

Heartbeat

MAY 29, 2023

In this article, we will explore the essential steps involved in training LLMs, including data preparation, model selection, hyperparameter tuning, and fine-tuning. We will also discuss best practices for training LLMs, such as using transfer learning, data augmentation, and ensembling methods.

Machine Learning 78

Machine Learning Machine Learning Natural Language Processing Data Preparation 78

PyImageSearch

JANUARY 23, 2023

The reasoning behind that is simple; whatever we have learned till now, be it adaptive boosting, decision trees, or gradient boosting, have very distinct statistical foundations which require you to get your hands dirty with the math behind them. The goal is to nullify the abstraction created by packages as much as possible.

Deep Learning 92

Deep Learning Deep Learning Algorithm Decision Trees 92

PyImageSearch

DECEMBER 12, 2022

Setting Up the Prerequisites Building the Model Assessing the Model Summary Citation Information Scaling Kaggle Competitions Using XGBoost: Part 2 In our previous tutorial , we went through the basic foundation behind XGBoost and learned how easy it was to incorporate a basic XGBoost model into our project. Table 1: The Dataset.

Decision Trees 52

Decision Trees Deep Learning Deep Learning Exploratory Data Analysis 52

Mlearning.ai

JANUARY 29, 2024

Data Science Project — Build a Decision Tree Model with Healthcare Data Using Decision Trees to Categorize Adverse Drug Reactions from Mild to Severe Photo by Maksim Goncharenok Decision trees are a powerful and popular machine learning technique for classification tasks.

Decision Trees 52

Decision Trees Data Science Exploratory Data Analysis Data Analysis 52