NYU Center for Data Science

AUGUST 29, 2024

Puli works on a variety of topics ranging from causal estimation and hypothesis testing to interpretability and survival analysis, but his primary research focus is on building machine learning models that are robust across populations, drawing on insights from causal inference. Standard algorithms aren’t designed for this scenario.

Hypothesis Testing 67

Hypothesis Testing Computer Science Computer Science Data Science 67

Towards AI

MAY 14, 2024

But there is one machine learning algorithm that seems to be causing waves when it comes to Artificial intelligence, yes it is popular among data scientists, but I want to view it from a geospatial point of view and see its capabilities. Its linear relationship concept makes sense and is simple to understand.

Machine Learning 105

Machine Learning Machine Learning Hypothesis Testing Algorithm 105

Pickl AI

DECEMBER 14, 2023

Hypothesis Testing Statistical hypothesis testing enables data scientists to validate assumptions and draw conclusions about populations based on sample data. Calculus Derivatives Derivatives are employed to understand how a function changes, aiding in the optimization of algorithms.

Data Science 52

Data Science Hypothesis Testing Machine Learning Machine Learning 52

ODSC - Open Data Science

DECEMBER 7, 2023

You’ll cover the integration of LLMs with advanced algorithms in DataGPT, with an emphasis on their collaborative roles in data analysis. You’ll take a deep dive into DataGPT’s technology stack, detailing its methodology for efficient data processing and its measures to ensure accuracy and consistency.

Data Science 98

Data Science Data Wrangling Machine Learning Machine Learning 98

Dataconomy

MAY 2, 2023

They design, develop, and deploy the machine learning algorithms that power everything from self-driving cars to personalized recommendations. They also develop algorithms that are utilized to sort through relevant data, and scale predictive models to best suit the amount of data pertinent to the business. They build the future.

ML 110

ML ML Machine Learning Machine Learning 110

Pickl AI

NOVEMBER 4, 2024

Mathematics is critical in Data Analysis and algorithm development, allowing you to derive meaningful insights from data. Statistics Understand descriptive statistics (mean, median, mode) and inferential statistics (hypothesis testing, confidence intervals). These concepts help you analyse and interpret data effectively.

Data Science 52

Data Science Python Machine Learning Machine Learning 52

Applied Data Science

AUGUST 2, 2021

They bring deep expertise in machine learning , clustering , natural language processing , time series modelling , optimisation , hypothesis testing and deep learning to the team. This allows for a much richer interpretation of predictions, without sacrificing the algorithm’s power.

Data Science 130

Data Science Data Scientist ML ML 130

Pickl AI

JUNE 9, 2024

Within the realm of Data Science, the following points highlight the integral connection between mathematics and its applications: The Backbone of Data Science Mathematics forms the fundamental basis of Data Science, enabling the development of robust algorithms and models to extract insights from data.

Data Science 52

Data Science Hypothesis Testing Data Scientist Machine Learning 52

Towards AI

JULY 15, 2023

Traditional methods for detecting fake accounts often rely on complex machine-learning algorithms. In this blog, I delve into the fascinating intersection of Benford’s Law and machine learning, exploring how this mathematical principle can be employed alongside advanced algorithms to expose and combat the presence of fake Twitter followers.

Machine Learning 96

Machine Learning Machine Learning Hypothesis Testing Algorithm 96

Data Science Dojo

JULY 3, 2024

Machine Learning : Supervised and unsupervised learning algorithms, including regression, classification, clustering, and deep learning. Statistics : Fundamental statistical concepts and methods, including hypothesis testing, probability, and descriptive statistics.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

Dataconomy

AUGUST 22, 2023

Today, as machine learning algorithms continue to shape our world, the integration of Bayesian principles has become a hallmark of advanced predictive modeling. Machine learning algorithms are like tools that help computers learn from data and make informed decisions or predictions. This is where machine learning comes in.

Machine Learning 91

Machine Learning Machine Learning Algorithm Deep Learning 91

Ocean Protocol

JANUARY 23, 2024

After a year of hypothesis testing, research sprints and over 20 different data challenges, hackathons, and data science experimentation: the top 10 data challenge participants, ranked by leaderboard points have emerged victorious. We are excited to announce the winners of our 2023 Data Challenge Championship and end-of-season rewards!

Hypothesis Testing 52

Hypothesis Testing Data Science Data Scientist Predictive Analytics 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. Differentiate between supervised and unsupervised learning algorithms.

Data Science 52

Data Science Cross Validation Machine Learning Machine Learning 52

Pickl AI

NOVEMBER 28, 2024

Summary: The blog discusses essential skills for Machine Learning Engineer, emphasising the importance of programming, mathematics, and algorithm knowledge. Understanding Machine Learning algorithms and effective data handling are also critical for success in the field.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Pickl AI

JANUARY 15, 2025

Hypothesis Testing Hypothesis testing is a vital aspect of statistics that allows data scientists to validate assumptions about a dataset. By using statistical tests, they can determine the significance of relationships between variables and draw conclusions based on sample data.

Data Scientist 52

Data Scientist Hypothesis Testing Data Analysis Data Analysis 52

Pickl AI

FEBRUARY 22, 2024

The curriculum includes Machine Learning Algorithms and prepares students for roles like Data Scientist, Data Analyst, System Analyst, and Intelligence Analyst. This bootcamp includes a dedicated Statistics module covering essential topics like types of variables, measures of central tendency, histograms, hypothesis testing, and more.

Data Science 52

Data Science Hypothesis Testing Data Analysis Data Analysis 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. Unsupervised Learning In this type of learning, the algorithm is trained on an unlabeled dataset, where no correct output is provided.

Data Science 75

Data Science Machine Learning Machine Learning Database 75

Pickl AI

MARCH 20, 2024

Proficiency in probability distributions, hypothesis testing, and statistical modelling enables Data Scientists to derive actionable insights from data with confidence and precision. Leveraging libraries such as Scikit-learn and TensorFlow, Data Scientists can implement machine learning algorithms with ease and precision.

Data Science 52

Data Science Data Scientist Data Wrangling Machine Learning 52

Pickl AI

APRIL 19, 2024

Neural Networks: Inspired by the human brain’s structure, neural networks are algorithms that allow machines to recognise patterns and make decisions based on input data. Finance: AI algorithms are used for fraud detection, risk assessment, and portfolio management, enhancing the efficiency and security of financial transactions.

Natural Language Processing 52

Natural Language Processing Machine Learning Machine Learning AI 52

Pickl AI

MAY 29, 2024

These skills encompass proficiency in programming languages, data manipulation, and applying Machine Learning Algorithms , all essential for extracting meaningful insights and making data-driven decisions. Machine Learning Algorithms Understanding and implementing Machine Learning Algorithms is a core requirement.

Data Scientist 52

Data Scientist Data Science Machine Learning Machine Learning 52

Pickl AI

JUNE 19, 2024

Here are some of the most common backgrounds that prepare you well: Mathematics and Statistics These disciplines provide a rock-solid understanding of data analysis, probability theory, statistical modelling, and hypothesis testing – all essential tools for extracting meaning from data.

Data Science 52

Data Science Data Scientist Hypothesis Testing Natural Language Processing 52

Pickl AI

JULY 10, 2023

It provides functions for descriptive statistics, hypothesis testing, regression analysis, time series analysis, survival analysis, and more. These packages extend the functionality of R by providing additional functions, algorithms, datasets, and visualizations.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Pickl AI

NOVEMBER 5, 2024

Data Science is an interdisciplinary field that uses scientific methods, algorithms, and systems to extract knowledge and insights from structured and unstructured data. For example, PayPal uses Machine Learning algorithms to analyse transaction patterns and identify anomalies that may indicate fraudulent activity.

Data Science 52

Data Science Artificial Intelligence Artificial Intelligence Machine Learning 52

Pickl AI

OCTOBER 14, 2024

Techniques Hypothesis Testing: Determining whether enough evidence supports a specific claim or hypothesis. Machine Learning: Utilising algorithms that improve predictions through learning from data. Techniques: Optimisation Algorithms: Identifying the most efficient way to achieve objectives.

Data Analysis 52

Data Analysis Data Analysis EDA Data Mining 52

Pickl AI

OCTOBER 15, 2024

Hypothesis Testing : Statistical Models help test hypotheses by analysing relationships between variables. These models help in hypothesis testing and determining the relationships between variables. Bayesian models and hypothesis tests (like t-tests or chi-square tests) are examples of inferential models.

Decision Trees 52

Decision Trees Hypothesis Testing Clustering Data Analysis 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. This phase entails meticulously selecting and training algorithms to ensure optimal performance. Evaluation tests the model’s performance using accuracy, precision, and recall metrics.

Data Analysis 52

Data Analysis Data Analysis Data Science Exploratory Data Analysis 52

Ocean Protocol

SEPTEMBER 9, 2024

They will quantify these impacts by calculating lap times, identifying strategic patterns, and validating their findings with hypothesis testing. Participants will use EDA and statistical analysis to understand how tire management and pit stop decisions impact race outcomes.

EDA 45

EDA Exploratory Data Analysis Hypothesis Testing Data Science 45

The MLOps Blog

MAY 31, 2023

From an algorithmic perspective, Learning To Rank (LeToR) and Elastic Search are some of the most popular algorithms used to build a Seach system. We can collect and use user-product historical interaction data to train recommendation system algorithms. are some examples. Let’s understand this with an example.

ML 59

ML ML Algorithm Machine Learning 59

Pickl AI

DECEMBER 10, 2024

A good book will also explain fundamental Machine Learning algorithms and their practical applications. Key Features: Comprehensive coverage of key topics like regression, sampling, and hypothesis testing. Key Features: Covers essential Machine Learning algorithms. Explains algorithms with clear visuals and examples.

Data Science 52

Data Science Python Machine Learning Machine Learning 52

Pickl AI

AUGUST 21, 2023

Software engineering concepts facilitate efficient data manipulation, enabling you to design algorithms, create visualizations, and build machine learning models. Concepts like probability, hypothesis testing, and regression analysis empower you to extract meaningful insights and draw accurate conclusions from data.

Data Scientist 52

Data Scientist Data Science Machine Learning Machine Learning 52

Pickl AI

SEPTEMBER 4, 2023

Statistical Analysis: Apply statistical techniques to analyse data, including descriptive statistics, hypothesis testing, regression analysis, and machine learning algorithms. This includes hypothesis testing , regression analysis, experimental design, and probability distributions.

Data Analysis 52

Data Analysis Data Analysis Hypothesis Testing Machine Learning 52

Ocean Protocol

JANUARY 25, 2024

2022 & 2023 data challenges tested different time durations between 7–30 days. It has been determined that initiatives and hypothesis testing that require longer than 20 days will be tagged and executed as something other than a data challenge (data science competition). continue to roll out regularly.

Data Science 52

Data Science Hypothesis Testing Data Scientist Predictive Analytics 52

Pickl AI

SEPTEMBER 12, 2024

A Algorithm: A set of rules or instructions for solving a problem or performing a task, often used in data processing and analysis. Decision Trees: A supervised learning algorithm that creates a tree-like model of decisions and their possible consequences, used for both classification and regression tasks.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52

Pickl AI

AUGUST 9, 2024

Statistical Analysis Introducing statistical methods and techniques for analysing data, including hypothesis testing, regression analysis, and descriptive statistics. Machine Learning Algorithms Basic understanding of Machine Learning concepts and algorithm s, including supervised and unsupervised learning techniques.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

Pickl AI

AUGUST 27, 2024

Statsmodels Allows users to explore data, estimate statistical models, and perform statistical tests. It is particularly useful for regression analysis and hypothesis testing. Pingouin A library designed for statistical analysis, providing a comprehensive collection of statistical tests.

Data Analysis 52

Data Analysis Data Analysis Python Data Analyst 52

Pickl AI

SEPTEMBER 23, 2024

Understanding Data Science Data Science is a multidisciplinary field that uses scientific methods, algorithms, and systems to extract knowledge and insights from structured and unstructured data. Finance In finance, Data Science is critical in fraud detection, risk management, and algorithmic trading.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Data Science Machine Learning 52

Pickl AI

JULY 23, 2023

It requires sophisticated tools and algorithms to derive meaningful patterns and trends from the sheer magnitude of data. Real-time data feeds and algorithmic trading strategies have transformed the dynamics of financial markets. Time series analysis finds applications in financial markets, weather forecasting, and sales forecasting.

Analytics 52

Analytics Analytics Predictive Analytics Data Analysis 52