Data Science Dojo

JULY 7, 2023

This discipline takes raw data, deciphers it, and turns it into a digestible format using various tools and algorithms. Tools such as Python, R, and SQL help to manipulate and analyze data. Understanding algorithms is like mastering maps, with each algorithm offering different paths to solutions.

Data Science 195

Data Science Data Scientist Python Decision Trees 195

Data Science Dojo

AUGUST 27, 2024

Python, R, and SQL: These are the most popular programming languages for data science. Algorithms: Decision trees, random forests, logistic regression, and more are like different techniques a detective might use to solve a case. Python, R, and SQL: These are the most popular programming languages for data science.

Data Scientist 195

Data Scientist Data Science Machine Learning Machine Learning 195

Towards AI

JULY 15, 2024

We shall look at various machine learning algorithms such as decision trees, random forest, K nearest neighbor, and naïve Bayes and how you can install and call their libraries in R studios, including executing the code. In addition, it’s also adapted to many other programming languages, such as Python or SQL.

Machine Learning 119

Machine Learning Machine Learning Algorithm K-nearest Neighbors 119

Dataconomy

JULY 24, 2023

Concepts such as linear algebra, calculus, probability, and statistical theory are the backbone of many data science algorithms and techniques. Coding skills are essential for tasks such as data cleaning, analysis, visualization, and implementing machine learning algorithms. Work Works with larger, more complex data sets.

Data Scientist 172

Data Scientist Data Science Data Analyst Machine Learning 172

Mlearning.ai

MARCH 19, 2023

What is the difference between `HAVING` and `WHERE` in a SQL query? The WHERE and HAVING clauses are both used in SQL queries to filter records based on specified conditions. Both algorithms create decision trees, and both are ‘ensemble’ models. The difference is in the underlying algorithm.

Machine Learning 52

Machine Learning Machine Learning Decision Trees SQL 52

IBM Journey to AI blog

JULY 6, 2023

Machine learning works on a known problem with tools and techniques, creating algorithms that let a machine learn from data through experience and with minimal human intervention. It’s unnecessary to know SQL, as programs are written in R, Java, SAS and other programming languages.

Machine Learning 70

Machine Learning Machine Learning Data Science Big Data 70

Pickl AI

JULY 18, 2023

SQL: Mastering Data Manipulation Structured Query Language (SQL) is a language designed specifically for managing and manipulating databases. While it may not be a traditional programming language, SQL plays a crucial role in Data Science by enabling efficient querying and extraction of data from databases.

Data Science 52

Data Science SQL Data Scientist Python 52

ODSC - Open Data Science

AUGUST 15, 2023

You’ll get hands-on practice with unsupervised learning techniques, such as K-Means clustering, and classification algorithms like decision trees and random forest. Finally, you’ll explore how to handle missing values and training and validating your models using PySpark. Free and paid passes are available now–register here.

Machine Learning 52

Machine Learning Machine Learning Data Science Data Scientist 52

Pickl AI

SEPTEMBER 12, 2024

A Algorithm: A set of rules or instructions for solving a problem or performing a task, often used in data processing and analysis. Decision Trees: A supervised learning algorithm that creates a tree-like model of decisions and their possible consequences, used for both classification and regression tasks.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52

Pickl AI

MARCH 20, 2024

Mastery of statistical concepts equips professionals to make informed decisions and draw accurate conclusions from empirical observations. Proficiency in programming languages Fluency in programming languages such as Python, R, and SQL is indispensable for Data Scientists.

Data Science 52

Data Science Data Scientist Data Wrangling Machine Learning 52

Mlearning.ai

MAY 23, 2023

An interdisciplinary field that constitutes various scientific processes, algorithms, tools, and machine learning techniques working to help find common patterns and gather sensible insights from the given raw input data using statistical and mathematical analysis is called Data Science. Decision trees are more prone to overfitting.

Data Science 52

Data Science Decision Trees Machine Learning 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. Differentiate between supervised and unsupervised learning algorithms.

Data Science 52

Data Science Cross Validation Machine Learning Machine Learning 52

Pickl AI

APRIL 26, 2024

It covers essential topics such as SQL queries, data visualization, statistical analysis, machine learning concepts, and data manipulation techniques. Key Takeaways SQL Mastery: Understand SQL’s importance, join tables, and distinguish between SELECT and SELECT DISTINCT. How do you join tables in SQL?

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52

phData

MAY 12, 2023

Its visual interface allows you to design workflows, handle data extraction and transformation, and apply statistical methods or machine learning algorithms. Moreover, Snowflake is designed to focus on simplicity, offering easy data loading, integration, and SQL-based data manipulation. Oh–and it’s free.

Data Warehouse 72

Data Warehouse Machine Learning Machine Learning Database 72

Pickl AI

FEBRUARY 4, 2024

Predictive Analytics: Leverage machine learning algorithms for accurate predictions. This makes Alteryx an indispensable tool for businesses aiming to glean insights and steer their decisions based on robust data. Users can effortlessly extract data from sources like SQL Server, Excel, Tableau, and even social media platforms.

Data Preparation 52

Data Preparation Tableau Data Visualization Analytics 52

phData

SEPTEMBER 10, 2024

Techniques include machine learning algorithms such as logistic regression, decision trees, and neural networks. To see this in action, we see a simple example of Snowflake Cortex using an SQL query that joins churn metrics and the top ten important model features. days, account_tenure_median = 5.01

Machine Learning 52

Machine Learning Machine Learning SQL Analytics 52

Pickl AI

DECEMBER 4, 2024

The field has evolved significantly from traditional statistical analysis to include sophisticated Machine Learning algorithms and Big Data technologies. Issues such as algorithmic bias, data privacy, and transparency are becoming critical topics of discussion within the industry.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

ODSC - Open Data Science

JANUARY 7, 2025

Just as a writer needs to know core skills like sentence structure and grammar, data scientists at all levels should know core data science skills like programming, computer science, algorithms, and soon. While knowing Python, R, and SQL is expected, youll need to go beyond that. Employers arent just looking for people who can program.

Data Scientist 40

Data Scientist Data Science Machine Learning Machine Learning 40

Pickl AI

MAY 31, 2023

Begin by employing algorithms for supervised learning such as linear regression , logistic regression, decision trees, and support vector machines. To obtain practical expertise, run the algorithms on datasets. You should be skilled in using a variety of tools including SQL and Python libraries like Pandas.

Data Science 52

Data Science Python Data Scientist Machine Learning 52

Pickl AI

AUGUST 9, 2024

Understanding the differences between SQL and NoSQL databases is crucial for students. Machine Learning Algorithms Basic understanding of Machine Learning concepts and algorithm s, including supervised and unsupervised learning techniques. Finance Applications in fraud detection, risk assessment, and algorithmic trading.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

Pickl AI

APRIL 28, 2023

Here is the tabular representation of the same: Technical Skills Non-technical Skills Programming Languages: Python, SQL, R Good written and oral communication Data Analysis: Pandas, Matplotlib, Numpy, Seaborn Ability to work in a team ML Algorithms: Regression Classification, Decision Trees, Regression Analysis Problem-solving capability Big Data: (..)

Data Scientist 52

Data Scientist Data Science Hypothesis Testing Decision Trees 52

How to Learn Machine Learning

DECEMBER 4, 2022

Programming a computer with artificial intelligence (Ai) allows it to make decisions on its own. Numerous techniques, such as but not limited to rule-based systems, decision trees, genetic algorithms, artificial neural networks, and fuzzy logic systems, can be used to do this.

AI 52

AI AI Machine Learning Machine Learning 52

Pickl AI

APRIL 3, 2025

Modeling & Algorithms: Applying statistical models (like regression, classification, clustering) or Machine Learning algorithms to identify deeper patterns, make predictions, or classify data points. to understand the data’s main characteristics, distributions, and relationships. This helps formulate hypotheses.

Data Analysis 52

Data Analysis Data Analysis Data Visualization EDA 52

DagsHub

APRIL 21, 2024

Autonomous Vehicles: Automotive companies are using ML models for autonomous driving systems including object detection, path planning, and decision-making algorithms. This is the reason why data scientists need to be actively involved in this stage as they need to try out different algorithms and parameter combinations.

Machine Learning 59

Machine Learning Machine Learning ML ML 59

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