ODSC - Open Data Science

NOVEMBER 5, 2024

Hypothesis Testing and Machine Learning Now here’s the kicker: when you do machine learning (including that simple linear regression above), you are in fact searching for hypotheses that identify relationships in the data. But we never achieve a 0% chance of any of these being random.

Hypothesis Testing 52

Hypothesis Testing Machine Learning Machine Learning Data Mining 52

Data Science Dojo

AUGUST 30, 2023

Statistical analysis and hypothesis testing Statistical methods provide powerful tools for understanding data. An Applied Data Scientist must have a solid understanding of statistics to interpret data correctly. Machine learning algorithms Machine learning forms the core of Applied Data Science.

Data Science 195

Data Science Hypothesis Testing Machine Learning Machine Learning 195

Data Science Dojo

JANUARY 16, 2023

Exploratory analysis Exploratory analysis involves consulting various data sets to see how certain variables may be related, or how certain patterns may be driving others. Diagnostic analytics includes methods such as hypothesis testing, determining a correlations v/s causation, and diagnostic regression analysis.

Data Analysis 195

Data Analysis Data Analysis Data Analyst Big Data 195

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

Towards AI

MARCH 17, 2023

Random variable: Statistics and data mining are concerned with data. How do we link sample spaces and events to data? One of the most important applications is hypothesis testing. [I I am going to write a separate blog on hypothesis testing, but till then, you can refer attached link.].

Hypothesis Testing 98

Hypothesis Testing Data Mining Data Mining Data Mining 98

Pickl AI

MAY 29, 2024

Summary: Data Science is becoming a popular career choice. Mastering programming, statistics, Machine Learning, and communication is vital for Data Scientists. A typical Data Science syllabus covers mathematics, programming, Machine Learning, data mining, big data technologies, and visualisation.

Data Scientist 52

Data Scientist Data Science Machine Learning Machine Learning 52

Pickl AI

AUGUST 27, 2024

Summary: Python simplicity, extensive libraries like Pandas and Scikit-learn, and strong community support make it a powerhouse in Data Analysis. It excels in data cleaning, visualisation, statistical analysis, and Machine Learning, making it a must-know tool for Data Analysts and scientists.

Data Analysis 52

Data Analysis Data Analysis Python Data Analyst 52