Dataconomy

MAY 16, 2023

They employ statistical and mathematical techniques to uncover patterns, trends, and relationships within the data. Data scientists possess a deep understanding of statistical modeling, data visualization, and exploratory data analysis to derive actionable insights and drive business decisions.

Data Scientist 156

Data Scientist ML ML Machine Learning 156

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. Things to be learned: Ensemble Techniques such as Random Forest and Boosting Algorithms and you can also learn Time Series Analysis.

Data Science 75

Data Science Machine Learning Machine Learning Database 75

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. Explain the concept of feature engineering in Maachine Learning. Here is a brief description of the same.

Data Science 52

Data Science Cross Validation Machine Learning Machine Learning 52

Pickl AI

NOVEMBER 27, 2024

Libraries like Pandas and NumPy offer robust tools for data cleaning, transformation, and numerical computing. Scikit-learn and TensorFlow dominate the Machine Learning landscape, providing easy-to-implement models for everything from simple regressions to deep learning.

Data Science 52

Data Science Python Machine Learning Machine Learning 52

Pickl AI

JULY 25, 2023

Their primary responsibilities include: Data Collection and Preparation Data Scientists start by gathering relevant data from various sources, including databases, APIs, and online platforms. They clean and preprocess the data to remove inconsistencies and ensure its quality. Big Data Technologies: Hadoop, Spark, etc.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Pickl AI

APRIL 26, 2024

I conducted thorough data validation, collaborated with stakeholders to identify the root cause, and implemented corrective measures to ensure data integrity. I would perform exploratory data analysis to understand the distribution of customer transactions and identify potential segments.

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52

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. Deep Learning : A subset of Machine Learning that uses Artificial Neural Networks with multiple hidden layers to learn from complex, high-dimensional data.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52