Pickl AI

NOVEMBER 4, 2024

Familiarity with basic programming concepts and mathematical principles will significantly enhance your learning experience and help you grasp the complexities of Data Analysis and Machine Learning. Basic Programming Concepts To effectively learn Python, it’s crucial to understand fundamental programming concepts.

Data Science 52

Data Science Python Machine Learning Machine Learning 52

Women in Big Data

APRIL 17, 2024

His expertise in Artificial Intelligence and Machine Learning and engaging teaching style made the workshop an enriching experience. The “From Data to Decisions” workshop provided a fantastic foundation for understanding how statistics bridge the gap to powerful machine learning applications.

Exploratory Data Analysis 52

Exploratory Data Analysis EDA Machine Learning Machine Learning 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. For Data Analysis you can focus on such topics as Feature Engineering , Data Wrangling , and EDA which is also known as Exploratory Data Analysis.

Data Science 75

Data Science Machine Learning Machine Learning Database 75

Pickl AI

OCTOBER 14, 2024

Exploratory Data Analysis (EDA) Exploratory Data Analysis (EDA) is an approach to analyse datasets to uncover patterns, anomalies, or relationships. The primary purpose of EDA is to explore the data without any preconceived notions or hypotheses. Clustering: Grouping similar data points to identify segments within the data.

Data Analysis 52

Data Analysis Data Analysis EDA Data Mining 52

Pickl AI

JULY 25, 2023

Proficient in programming languages like Python or R, data manipulation libraries like Pandas, and machine learning frameworks like TensorFlow and Scikit-learn, data scientists uncover patterns and trends through statistical analysis and data visualization. Data Visualization: Matplotlib, Seaborn, Tableau, etc.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 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. Explain the bias-variance tradeoff in Machine Learning. Here is a brief description of the same.

Data Science 52

Data Science Cross Validation Machine Learning Machine Learning 52

Pickl AI

MAY 30, 2024

Developing predictive models using Machine Learning Algorithms will be a crucial part of your role, enabling you to forecast trends and outcomes. Also Read: Explore data effortlessly with Python Libraries for (Partial) EDA: Unleashing the Power of Data Exploration. Use statistical methods to identify and remove these anomalies.

Data Analysis 52

Data Analysis Data Analysis Data Science Exploratory Data Analysis 52