KDnuggets

AUGUST 26, 2019

Understanding Decision Trees for Classification in Python; How to Become More Marketable as a Data Scientist; Is Kaggle Learn a Faster Data Science Education? Also: Deep Learning for NLP: Creating a Chatbot with Keras!;

Data Scientist 127

Data Scientist Decision Trees Deep Learning Deep Learning 127

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 273

Data Scientist Data Science Machine Learning Machine Learning 273

Data Science Dojo

JULY 7, 2023

Tools such as Python, R, and SQL help to manipulate and analyze data. Data scientists need a strong foundation in statistics and mathematics to understand the patterns in data. Proficiency in tools like Python, R, SQL, and platforms like Hadoop or Spark is essential for data manipulation and analysis.

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

Dataconomy

JULY 24, 2023

” Data management and manipulation Data scientists often deal with vast amounts of data, so it’s crucial to understand databases, data architecture, and query languages like SQL. It involves developing algorithms that can learn from and make predictions or decisions based on data. Works with smaller data sets.

Data Scientist 172

Data Scientist Data Science Data Analyst Machine Learning 172

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

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. Photo by Marvin Meyer on Unsplash 1.

Machine Learning 52

Machine Learning Machine Learning Decision Trees SQL 52

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

Heartbeat

OCTOBER 31, 2023

Before continuing, revisit the lesson on decision trees if you need help understanding what they are. We can compare the performance of the Bagging Classifier and a single Decision Tree Classifier now that we know the baseline accuracy for the test dataset. Bagging is a development of this idea.

Decision Trees 52

Decision Trees Deep Learning Deep Learning Cross Validation 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

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. Machine learning models are often employed to predict churn.

Machine Learning 52

Machine Learning Machine Learning SQL Analytics 52

Pickl AI

FEBRUARY 4, 2024

Unlike SQL, Alteryx offers a visually intuitive approach, allowing users to focus on analysis without being encumbered by technical intricacies. Users can effortlessly extract data from sources like SQL Server, Excel, Tableau, and even social media platforms. Alteryx’s core features 1.

Data Preparation 52

Data Preparation Tableau Data Visualization Analytics 52

The MLOps Blog

JANUARY 26, 2024

Some ML systems use deep learning, while others utilize more classical models like decision trees or XGBoost. They have a non-static data source (new data will arrive at some cadence), train an ML model to solve a prediction problem, and have a user interface that allows users to consume the predictions.

Machine Learning 72

Machine Learning Machine Learning ML ML 72

IBM Journey to AI blog

JULY 6, 2023

The fields have evolved such that to work as a data analyst who views, manages and accesses data, you need to know Structured Query Language (SQL) as well as math, statistics, data visualization (to present the results to stakeholders) and data mining. It’s also necessary to understand data cleaning and processing techniques.

Machine Learning 70

Machine Learning Machine Learning Data Science Big Data 70

Pickl AI

SEPTEMBER 12, 2024

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. Random Forest: An ensemble learning method that constructs multiple decision trees and merges them to improve accuracy and control overfitting.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52

phData

MAY 12, 2023

Moreover, Snowflake is designed to focus on simplicity, offering easy data loading, integration, and SQL-based data manipulation. This could involve a range of techniques, such as logistic regression, decision trees, or even more advanced methods like neural networks. How Does KNIME & Snowflake Work Together?

Data Warehouse 72

Data Warehouse Machine Learning Machine Learning Database 72

Mlearning.ai

MAY 23, 2023

Decision trees are more prone to overfitting. Some algorithms that have low bias are Decision Trees, SVM, etc. Hence, we have various classification algorithms in machine learning like logistic regression, support vector machine, decision trees, Naive Bayes classifier, etc. character) is underlined or not.

Data Science 52

Data Science Decision Trees 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

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

MAY 31, 2023

Begin by employing algorithms for supervised learning such as linear regression , logistic regression, decision trees, and support vector machines. You should be skilled in using a variety of tools including SQL and Python libraries like Pandas. It includes regression, classification, clustering, decision trees, and more.

Data Science 52

Data Science Python Data Scientist Machine Learning 52

Pickl AI

FEBRUARY 12, 2024

Here are some key areas often assessed: Programming Proficiency Candidates are often tested on their proficiency in languages such as Python, R, and SQL, with a focus on data manipulation, analysis, and visualization.

Data Science 52

Data Science Cross Validation Machine Learning Machine Learning 52

Pickl AI

DECEMBER 4, 2024

Grasp the Fundamentals of Data Analysis and Management Build a strong foundation in Data Analysis by learning data manipulation techniques using SQL and Excel. Focus on Python and R for Data Analysis, along with SQL for database management. This foundational knowledge is essential for any Data Science project.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

ODSC - Open Data Science

JANUARY 7, 2025

While knowing Python, R, and SQL is expected, youll need to go beyond that. Similar to previous years, SQL is still the second most popular skill, as its used for many backend processes and core skills in computer science and programming. Employers arent just looking for people who can program.

Data Scientist 40

Data Scientist Data Science Machine Learning Machine Learning 40

Pickl AI

APRIL 3, 2025

Modeling: Build a logistic regression or decision tree model to predict the likelihood of a customer churning based on various factors. Recommends actions to achieve desired outcomes (e.g., suggesting optimal pricing strategies, recommending specific marketing interventions).

Data Analysis 52

Data Analysis Data Analysis Data Visualization EDA 52

Pickl AI

AUGUST 9, 2024

Understanding the differences between SQL and NoSQL databases is crucial for students. Key topics include: Supervised Learning Understanding algorithms such as linear regression, decision trees, and support vector machines, and their applications in Big Data.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

DagsHub

APRIL 21, 2024

It offers implementations of various machine learning algorithms, including linear and logistic regression , decision trees , random forests , support vector machines , clustering algorithms , and more. It is an open-source tool that is free to use without any licensing costs.

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