Pickl AI

AUGUST 9, 2024

Summary: A comprehensive Big Data syllabus encompasses foundational concepts, essential technologies, data collection and storage methods, processing and analysis techniques, and visualisation strategies. Fundamentals of Big Data Understanding the fundamentals of Big Data is crucial for anyone entering this field.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

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. What is cross-validation, and why is it used in Machine Learning?

Data Science 52

Data Science Cross Validation Machine Learning Machine Learning 52

Pickl AI

NOVEMBER 28, 2024

Concepts such as probability distributions, hypothesis testing , and Bayesian inference enable ML engineers to interpret results, quantify uncertainty, and improve model predictions. Big Data Tools Integration Big data tools like Apache Spark and Hadoop are vital for managing and processing massive datasets.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Pickl AI

FEBRUARY 22, 2024

MicroMasters Program in Statistics and Data Science MIT – edX 1 year 2 months (INR 1,11,739) This program integrates Data Science, Statistics, and Machine Learning basics. It emphasises probabilistic modeling and Statistical inference for analysing big data and extracting information.

Data Science 52

Data Science Hypothesis Testing Data Analysis Data Analysis 52

Pickl AI

SEPTEMBER 12, 2024

B Big Data : Large datasets characterised by high volume, velocity, variety, and veracity, requiring specialised techniques and technologies for analysis. Clustering: An unsupervised Machine Learning technique that groups similar data points based on their inherent similarities.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52

Mlearning.ai

MAY 23, 2023

This data can be used to pass as an input to the neural network maintaining a small batch size. The steps for SVM are given below: For SVM, small data sets can be obtained. This can be done by dividing the big data set. The subset of the data set can be obtained as an input if using the partial fit function.

Data Science 52

Data Science Decision Trees Machine Learning Machine Learning 52

Pickl AI

APRIL 26, 2024

Overfitting occurs when a model learns the training data too well, including noise and irrelevant patterns, leading to poor performance on unseen data. Techniques such as cross-validation, regularisation , and feature selection can prevent overfitting. In my previous role, we had a project with a tight deadline.

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52