Data Science Dojo

AUGUST 11, 2023

The ability to understand the principles of probability, hypothesis testing, and confidence intervals enables data scientists to validate their findings and ascertain the reliability of their analyses. It provides a wide range of mathematical functions and algorithms. SciPy is a library for scientific computing.

Data Science 195

Data Science Python Data Scientist Decision Trees 195

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

MARCH 20, 2024

Proficiency in probability distributions, hypothesis testing, and statistical modelling enables Data Scientists to derive actionable insights from data with confidence and precision. Mastery of statistical concepts equips professionals to make informed decisions and draw accurate conclusions from empirical observations.

Data Science 52

Data Science Data Scientist Data Wrangling Data Visualization 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

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. It includes regression, classification, clustering, decision trees, and more.

Data Science 52

Data Science Python Data Scientist Machine Learning 52

Pickl AI

APRIL 26, 2024

Then, I would explore forecasting models such as ARIMA, exponential smoothing, or machine learning algorithms like random forests or gradient boosting to predict future sales. Advanced Technical Questions Machine Learning Algorithms What is logistic regression, and when is it used?

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52

DataRobot Blog

MAY 26, 2022

These methods provided the benefit of being supported by rich literature on the relevant statistical tests to confirm the model’s validity—if a validator wanted to confirm that the input predictors of a regression model were indeed relevant to the response, they need only to construct a hypothesis test to validate the input.

ML 52

ML ML Machine Learning Machine Learning 52