Data Science Dojo

JANUARY 16, 2023

An overview of data analysis, the data analysis process, its various methods, and implications for modern corporations. Studies show that 73% of corporate executives believe that companies failing to use data analysis on big data lack long-term sustainability.

Data Analysis 195

Data Analysis Data Analysis Data Analyst Big Data 195

Pickl AI

OCTOBER 14, 2024

Summary: This article explores different types of Data Analysis, including descriptive, exploratory, inferential, predictive, diagnostic, and prescriptive analysis. Introduction Data Analysis transforms raw data into valuable insights that drive informed decisions. What is Data Analysis?

Data Analysis 52

Data Analysis Data Analysis EDA Data Mining 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. Why Python?

Data Analysis 52

Data Analysis Data Analysis Python Data Analyst 52

Pickl AI

NOVEMBER 4, 2024

This article will guide you through effective strategies to learn Python for Data Science, covering essential resources, libraries, and practical applications to kickstart your journey in this thriving field. Key Takeaways Python’s simplicity makes it ideal for Data Analysis. in 2022, according to the PYPL Index.

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

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. Domain-specific knowledge enhances relevance.

Data Scientist 52

Data Scientist Data Science Machine Learning Machine Learning 52

Pickl AI

MARCH 3, 2023

There are other types of Statistical Analysis as well which includes the following: Predictive Analysis: Significantly, it is the type of Analysis useful for forecasting future events based on present and past data. Moreover, it helps make informed decisions and encourages efficient decision-making processes.

Exploratory Data Analysis 40

Exploratory Data Analysis Hypothesis Testing Data Analyst Data Scientist 40