Augustus_loyola

image
  • 6942
    Rank
  • 0
    Points

  • Badges

  • Likes

  • Hackathon
  • 0
    Articles

Badges

No badges found from Blog

No badges on discuss

No badges earned on Datahack

About Augustus_loyola

Member Since Sept. 24, 2016, 8:57 p.m.
Location chennai
Area of Interest Statistics Analysis, Machine Learning & Data Mining

Activity

No blogs found

No Discussions found
Participated in Skilltest: Regression and secured rank 412
Participated in DataHour: Continuous Testing and Evaluation with LLMs
Participated in DataHour: Harnessing ML and NLP for Elevated Customer Experiences
Participated in DataHour: Demystifying Demand Forecasting for Retail Success
Participated in DataHour: Unwritten Rules for Success in Machine Learning
Participated in DataHour: Why Did My AI Do That? Decoding Decision-Making in ML
Participated in DataHour: Machine Learning Tips and Tricks
Participated in DataHour: From APIs to Insights: Building Custom Power BI Connectors for RESTful APIs
Participated in DataHour: Handling Satellite and Geospatial Raster Data in Python
Participated in DataHour: Titanic Machine Learning Case Study using Python
Participated in DataHour: Industrial Application of Large Language Models like ChatGPT
Participated in DataHour: Statistics with Python for Data Science
Participated in DataHour: Exploring Dimensionality Reduction
Participated in DataHour: Web Scraping using Python Libraries
Participated in DataHour: Introduction to Social Network Analysis
Participated in DataHour: Understanding Logistic Regression and Decision Tree Analysis
Participated in DataHour: Building an End-to-End Solution for Big Mart Sales Prediction
Participated in DataHour: Unlocking Business Growth - The Power of Customer Segmentation
Participated in DataHour: An Introduction to Machine Learning with Sequence Data
Participated in DataHour: FIFA World Cup Match Analysis Using Python
Participated in DataHour: Personalizing Demand Planning Using Scenario Analysis
Participated in DataHour: ChatGPT and the Future of NLP Systems
Participated in DataHour: Getting Started with Python
Participated in DataHour: Generating Labeled Data through Weak Supervision
Participated in DataHour: Feature Engineering and Selection for Machine Learning
Participated in DataHour: Best of Pandas & The Power of Simple Models
Participated in DataHour: Application of Data Science in Insurance Industry
Participated in DataHour: Machine Learning on Live Streaming Data for AIOps
Participated in DataHour: Evaluation Criteria for Validating Machine Learning Models
Participated in DataHour: Forecasting & Time-series Analysis
Participated in DataHour: Boosting Performance with Ensemble Methods
Participated in DataHour: Feature Engineering and benefits of EDA
Participated in DataHour: How Good is AI for Conversations?
Participated in DataHour: Constructing Machine Learning Pipelines using Scikit-learn
Participated in DataHour: Transforming HR with People Analytics
Participated in DataHour: Application of ML Classification Techniques in Banking Industry
Participated in DataHour: How to Forecast New Product Launches using Data Centric Approach
Participated in DataHour: Everything You Need to Know About Pandas
Participated in DataHour: Data Science in Banking Industry
Participated in DataHour: Understanding Energy Industry through EDA
Participated in DataHour: Metrics in Tech - Using Data to Drive Business Decisions
Participated in DataHour: Exploring the Best Book Sellers Dataset
Participated in DataHour: Solving Business Problems with Microsoft Excel
Participated in DataHour: Data Preparation and Feature Engineering in ML
Participated in DataHour: Unlocking the Power of Embeddings
Participated in DataHour: A/B testing - Theory, Practice and Pitfalls
Participated in DataHour: Understanding Graph Data Science
Participated in DataHour: Dealing with Imbalanced Datasets in ML Classification Problems
Participated in DataHour: Salary Analysis and Prediction Using ML
Participated in DataHour: Data Wrangling Using Geospatial Data in Python
Participated in DataHour: Diabetic Patients’ Readmission Prediction using ML
Participated in DataHour: No-code ML Hands-on using Orange Data Mining Tool
Participated in DataHour: Deep Dive into Semantic Segmentation- Techniques, Challenges and State-of-the-Art
Participated in Identify the apparels (Fashion MNIST)
Participated in Internship Challenge - Analytics Vidhya (Data Science)
Participated in Black Friday Sales Prediction
Participated in Internship Challenge Round 2- Analytics Vidhya (Data Science)
Participated in What's Your Story 2?
Participated in Internship Challenge - Analytics Vidhya (Web Development)
Participated in Practice Problem: Strategic Thinking II
Participated in Data Science Interview Preparation Test
Participated in Experiments with Data
Participated in Identify the Digits (MNIST)
Participated in Big Mart Sales Prediction
Participated in Age Detection of Actors
Participated in Practice Problem: Intel Scene Classification Challenge
Participated in Time Series Forecasting
Participated in Practice Problem: Urban Sound Classification
Participated in Twitter Sentiment Analysis
Participated in India ML Hiring Hackathon 2019
Participated in AmExpert 2019 – Machine Learning Hackathon
Participated in LTFS Data Science FinHack 2
Participated in DataHour: Data to Insightful Actions with No Code AI
Participated in DataHour: Methods for Explaining the Blackbox of Machine Learning Model
Participated in DataHour: Data Management and AI
Participated in DataHour: Everything You Need to Know About Numpy
Participated in DataHour: An Introduction to Central Limit Theorem
Participated in DataHour: ML Model Interpretation and Evaluation
Participated in DataHour: Unfolding Model Evaluation Metrics in Machine Learning
Participated in DataHour: An Introduction to Measuring Marketing Channel Effectiveness
Participated in DataHour: Artificial Intelligence Approach in Stock Market Analysis
Participated in DataHour: Ensemble Techniques in Machine Learning
Participated in DataHour: AI/ML Era in Customer Experience (CX)
Participated in DataHour: Introduction to Federated Learning
Participated in DataHour: Introduction to Classification using Azure Machine Learning
Participated in DataHour: Hypothesis Testing A-Z
Participated in DataHour: Making AI work for Business
Participated in A Practical Approach to Kaggle Competition
Participated in DataHour: How to Approach an ML Problem Statement from Scratch
Participated in DataHour: Applications of Optimization in On-demand Food and Grocery Delivery
Participated in DataHour: Netflix Data Analysis using Python
Participated in DataHour: Exploratory Data Analysis with F#
Participated in DataHour: The Art of Feature Engineering
Participated in DataHour: Causal Experimentations - When A/B Test is Not Possible
Participated in DataHour: Introduction to Positive Unlabelled(PU) Learning
Participated in DataHour: Introduction and Hands-on workshop with Reinforcement Learning
Participated in DataHour: Using Data Science Methodology to Assess Equity in Communication
Participated in DataHour: Customer Data Science Models - Retail and CPG
Participated in DataHour: Data Science Use Cases
Participated in DataHour: Need for Self Supervised Learning - Practice at SAP
Participated in DataHour: Applications of Machine Learning in Self Driving Cars
Participated in DataHour: Diving into the field of Data Analytics
Participated in DataHour: How to start your Kaggle journey?
Participated in DataHour: Practical Hypothesis Testing
Participated in DataHour: Steps before using an ML Model
Participated in DataHour: Statistics in Data Science
Participated in DataHour: Understanding Dimensionality Reduction
Participated in DataHour: Data Science Use Cases - Part 2
Participated in DataHour: An Empathetic AI for Healthcare
Participated in DataHour: HIV Analysis using ML and Flutter
Participated in DataHour: Churn Analytics in Telcos
Participated in DataHour: An Introduction to Extended Reality (XR)
Participated in DataHour: Python Data Structures
Participated in DataHour: Exploring Heart Disease Data using Python
Participated in DataHour: Evaluation Measures for Binary Classification
Participated in DataHour: Quantum Computing in Financial Industry
Participated in DataHour: How Data Science is used in Fintech?
Participated in DataHour: Building and Operationalizing an Explainable Predictive Model
Participated in DataHour: Importance of Statistics in Data Science and Machine Learning
Participated in DataHour: How do Algorithms Generate Recommendations?
Participated in DataHour: Classification Algorithms Evaluation Metrics
Participated in DataHour: Advanced Exploratory Data Analysis on Credit Data
Participated in DataHour: Exploring Multi-label & Multi-class Classification
Participated in DataHour: Normal Distribution - Understanding the Numbers and its Real Life Applications
Participated in DataHour: Diabetes Prediction Using Survival Analysis
Participated in DataHour: Machine Learning Model Development using Pandas, Numpy and Scikit-Learn
Participated in DataHour: Analyzing Loan Application Data using Python
Participated in DataHour: Transforming Business Challenges into Data Driven Solution
Participated in DataHour: Hyperparameter Optimization Demystified
Participated in DataHour: Introduction to Optimization using Genetic Algorithms
Participated in DataHour: Understanding Logistic Regression
Participated in DataHour: Anomaly Detection in Time Series Data
Participated in DataHour: Real-time Machine Learning - Challenges and Solution
Participated in DataHour: Understanding ChatGPT and its Use Cases
Participated in DataHour: Experiments with Interpretable Artificial Intelligence
Participated in DataHour: Basic Concepts of Object Oriented Programming in Python
Support

We use cookies essential for this site to function well. Please click to help us improve its usefulness with additional cookies. Learn about our use of cookies in our Privacy Policy.

Feedback

We believe in making Analytics Vidhya the best experience possible for Data Science enthusiasts. Help us by providing valuable Feedback.