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. Differentiate between supervised and unsupervised learning algorithms.

Data Science 52

Data Science Cross Validation Machine Learning Machine Learning 52

ODSC - Open Data Science

APRIL 3, 2023

Skills like effective verbal and written communication will help back up the numbers, while data visualization (specific frameworks in the next section) can help you tell a complete story. Data Wrangling: Data Quality, ETL, Databases, Big Data The modern data analyst is expected to be able to source and retrieve their own data for analysis.

Analytics 52

Analytics Analytics Data Analyst SQL 52

Pickl AI

JULY 18, 2023

They possess a deep understanding of AI technologies, algorithms, and frameworks and have the ability to translate business requirements into robust AI systems. AI Engineers focus primarily on implementing and deploying AI models and algorithms, working closely with data scientists and machine learning experts.

AI 52

AI AI Machine Learning Machine Learning 52

Pickl AI

AUGUST 21, 2023

The Data Science Roadmap: Navigating Your Path to Success Step 1: Learning About Programming or Software Engineering A strong foundation in programming languages like Python , R, or Java is essential. Step 2: Acquiring Statistical Proficiency A Data Scientist’s toolkit is incomplete without a solid understanding of statistics.

Data Scientist 52

Data Scientist Data Science Machine Learning Machine Learning 52

Dataconomy

MAY 16, 2023

A machine learning engineer focuses on implementing and deploying machine learning models into production systems. They possess strong programming and engineering skills to develop scalable and efficient machine learning solutions.

Data Scientist 156

Data Scientist ML ML Machine Learning 156

Pickl AI

JULY 18, 2023

By transitioning from computer science to data science, you can tap into a broader range of job opportunities and potentially increase your earning potential. Leveraging existing skills: Computer science provides a strong foundation in programming, algorithms, and problem-solving, which are highly valuable in data science.

Computer Science 52

Computer Science Computer Science Data Science Machine Learning 52

Pickl AI

JULY 20, 2023

Predictive Analytics Projects: Predictive analytics involves using historical data to predict future events or outcomes. Techniques like regression analysis, time series forecasting, and machine learning algorithms are used to predict customer behavior, sales trends, equipment failure, and more. ImageNet).

Analytics 40

Analytics Analytics Big Data Big Data 40

ODSC - Open Data Science

MARCH 3, 2023

Recently, we spoke with Pedro Domingos, Professor of computer science at the University of Washington, AI researcher, and author of “The Master Algorithm” book. In the interview, we talked about the quest for the “ultimate machine learning algorithm.” It learns from text, images, and robot actions, and then it learns what to do.

Machine Learning 52

Machine Learning Machine Learning Algorithm Data Science 52

ODSC - Open Data Science

JANUARY 29, 2024

Open Source ML/DL Platforms: Pytorch, Tensorflow, and scikit-learn Hiring managers continue to favor the most popular open-source machine/deep learning platforms including Pytorch, Tensorflow, and scikit-learn. This versatility allows prompt engineers to adapt it to different projects and needs.

Machine Learning 52

Machine Learning Machine Learning Data Science Natural Language Processing 52

Becoming Human

MAY 15, 2023

There is a position called Data Analyst whose work is to analyze the historical data, and from that, they will derive some KPI s (Key Performance Indicators) for making any further calls. 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

Heartbeat

DECEMBER 27, 2023

The machine learning (ML) lifecycle defines steps to derive values to meet business objectives using ML and artificial intelligence (AI). scikit-learn==1.1.1 Here are some details about these packages: jupyterlab is for model building and data exploration. catboost is the machine learning algorithm for model building.

Machine Learning 52

Machine Learning Machine Learning Python ML 52