Pickl AI

NOVEMBER 5, 2024

Introduction Data Science and Artificial Intelligence (AI) are at the forefront of technological innovation, fundamentally transforming industries and everyday life. What is Data Science and Artificial Intelligence? The impact is profound and far-reaching.

Data Science 52

Data Science Artificial Intelligence Artificial Intelligence Machine Learning 52

Pickl AI

JULY 10, 2023

Hence, you can use R for classification, clustering, statistical tests and linear and non-linear modelling. It provides functions for descriptive statistics, hypothesis testing, regression analysis, time series analysis, survival analysis, and more. How is R Used in Data Science?

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Ocean Protocol

SEPTEMBER 9, 2024

They will quantify these impacts by calculating lap times, identifying strategic patterns, and validating their findings with hypothesis testing. Participants will use EDA and statistical analysis to understand how tire management and pit stop decisions impact race outcomes.

EDA 45

EDA Exploratory Data Analysis Hypothesis Testing Data Science 45

Pickl AI

AUGUST 9, 2024

Some of the most notable technologies include: Hadoop An open-source framework that allows for distributed storage and processing of large datasets across clusters of computers. Statistical Analysis Introducing statistical methods and techniques for analysing data, including hypothesis testing, regression analysis, and descriptive statistics.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

Pickl AI

OCTOBER 14, 2024

Clustering: Grouping similar data points to identify segments within the data. Techniques Hypothesis Testing: Determining whether enough evidence supports a specific claim or hypothesis. Techniques like mean, median, standard deviation, and hypothesis testing are crucial for identifying patterns and trends in data.

Data Analysis 52

Data Analysis Data Analysis EDA Data Mining 52

Pickl AI

SEPTEMBER 12, 2024

A/B Testing: A statistical method for comparing two versions of a variable to determine which one performs better. Artificial Intelligence (AI): A branch of computer science focused on creating systems that can perform tasks typically requiring human intelligence.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52

Pickl AI

JULY 25, 2023

Together, data engineers, data scientists, and machine learning engineers form a cohesive team that drives innovation and success in data analytics and artificial intelligence. These models may include regression, classification, clustering, and more. Data Visualization: Matplotlib, Seaborn, Tableau, etc.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

Becoming Human

MAY 15, 2023

In Inferential Statistics, you can learn P-Value , T-Value , Hypothesis Testing , and A/B Testing , which will help you to understand your data in the form of mathematics. In Descriptive Statistics, you need to focus on topics like Mean , Median , Mode, and Standard Deviation.

Data Science 75

Data Science Machine Learning Machine Learning Database 75

Pickl AI

MAY 31, 2023

Explore Machine Learning with Python: Become familiar with prominent Python artificial intelligence libraries such as sci-kit-learn and TensorFlow. After that, move towards unsupervised learning methods like clustering and dimensionality reduction. It includes regression, classification, clustering, decision trees, and more.

Data Science 52

Data Science Python Data Scientist Machine Learning 52

Pickl AI

DECEMBER 4, 2024

Concepts such as probability distributions, hypothesis testing, and regression analysis are fundamental for interpreting data accurately. This includes supervised learning techniques like linear regression and unsupervised learning methods like clustering.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Pickl AI

APRIL 26, 2024

Machine learning is a subset of artificial intelligence that enables computers to learn from data and improve over time without being explicitly programmed. Then, I would use clustering techniques such as k-means or hierarchical clustering to group customers based on similarities in their purchasing behaviour.

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52

Mlearning.ai

MAY 23, 2023

There are majorly two categories of sampling techniques based on the usage of statistics, they are: Probability Sampling techniques: Clustered sampling, Simple random sampling, and Stratified sampling. What is the p-value and what does it indicate in the Null Hypothesis? List down the conditions for Overfitting and Underfitting.

Data Science 52

Data Science Decision Trees Machine Learning Machine Learning 52