📌 5 Habits That Made Me A Data Scientist

🗂 Category: CODING

🕒 Date: 2024-06-28 | ⏱️ Read time: 7 min read

Advice and tips on becoming a data scientist

📌 Demonstrating Prioritization Effectiveness in Sales

🗂 Category:

🕒 Date: 2024-06-28 | ⏱️ Read time: 6 min read

The power of machine learning for contact priorization

📌 System Design: Load Balancer

🗂 Category:

🕒 Date: 2024-06-28 | ⏱️ Read time: 9 min read

Orchestrating strategies for optimal workload distribution in microservice applications

📌 CRAG – Intuitively and Exhaustively Explained

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2024-06-28 | ⏱️ Read time: 13 min read

Defining the Limits of Retrieval Augmented Generation

📌 Estimate the unobserved – Moving-Average Model Estimation with Maximum Likelihood in Python

🗂 Category: DATA SCIENCE

🕒 Date: 2024-06-28 | ⏱️ Read time: 8 min read

How unobserved covariates’ coefficients can be estimated with MLE

📌 Diving Deep into AutoGen and Agentic Frameworks

🗂 Category:

🕒 Date: 2024-06-28 | ⏱️ Read time: 13 min read

This blog post will go into the details of the “AutoGen: Enabling Next-Gen LLM Applications…

📌 Safeguarding Demand Forecasting with Causal Graphs

🗂 Category: DATA SCIENCE

🕒 Date: 2024-06-28 | ⏱️ Read time: 11 min read

Causal AI, exploring the integration of causal reasoning into machine learning

📌 The History of Convolutional Neural Networks for Image Classification (1989- Today)

🗂 Category: DEEP LEARNING

🕒 Date: 2024-06-28 | ⏱️ Read time: 18 min read

A tour through the history of Computer Vision!

📌 The Math Behind Risk – Part 1

🗂 Category: DATA SCIENCE

🕒 Date: 2024-06-28 | ⏱️ Read time: 11 min read

Does the attack really have an advantage in the game of world conquest?

📌 I Invented a Way to Speak to an AI, Keeping Your Privacy

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2024-06-28 | ⏱️ Read time: 9 min read

The tech is called “Silent Voice.”

📌 Understanding Transformers

🗂 Category: DEEP LEARNING

🕒 Date: 2024-06-27 | ⏱️ Read time: 12 min read

A straightforward breakdown of “Attention is All You Need”¹

📌 Prompt Engineering: Tips, Approaches, and Future Directions

🗂 Category: DATA SCIENCE

🕒 Date: 2024-06-27 | ⏱️ Read time: 5 min read

Our weekly selection of must-read Editors’ Picks and original features

📌 Classification Loss Functions: Intuition and Applications

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2024-06-27 | ⏱️ Read time: 9 min read

A simpler way to understand derivations of loss functions for classification and when/how to apply…

📌 3 Challenges to Being a Data Scientist in 2024

🗂 Category: CAREER ADVICE

🕒 Date: 2024-06-27 | ⏱️ Read time: 7 min read

Given the current climate, is data science for you?

📌 A Complete Guide to Master Step Functions on AWS

🗂 Category: SCIENCE AND TECHNOLOGY

🕒 Date: 2024-06-27 | ⏱️ Read time: 10 min read

Workflow orchestration made easier

📌 The Ultimate Guide to Finding Outliers in Your Time-Series Data (Part 2)

🗂 Category: DATA SCIENCE

🕒 Date: 2024-06-26 | ⏱️ Read time: 1 min read

Effective machine learning methods and tools for outlier detection in time-series analysis

📌 How Bend Works: A Parallel Programming Language That “Feels Like Python but Scales Like CUDA”

🗂 Category:

🕒 Date: 2024-06-26 | ⏱️ Read time: 26 min read

A brief introduction to Lambda Calculus, Interaction Combinators, and how they are used to parallelize…

📌 Business Planning with Python – Revenue Optimization

🗂 Category: BUSINESS

🕒 Date: 2024-06-26 | ⏱️ Read time: 14 min read

How can you use data analytics to help small businesses maximize their revenue while maintaining…

📌 The Intuitive Basics of Optimization

🗂 Category: DATA SCIENCE

🕒 Date: 2024-06-26 | ⏱️ Read time: 14 min read

A gentle introduction to the amazing field of optimization

📌 Improving RAG Performance Using Rerankers

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2024-06-25 | ⏱️ Read time: 11 min read

A tutorial on using rerankers to improve your RAG pipeline

📌 Making LLMs Write Better and Better Code for Self-Driving Using LangProp

🗂 Category: CHATGPT

🕒 Date: 2024-06-25 | ⏱️ Read time: 11 min read

Analogy from classical machine learning: LLM (Large Language Model) = optimizer; code = parameters; LangProp…