Logo: 
Areas Served: The Importance of Having a Portfolio As a Data Scientist
Author(s): Youssef Hosni Originally published on Towards AI. Unleashing the Power of Data Science Portfolios: Elevate Your Career and Stand Out in the Job Market In today’s competitive job market, simply having a degree in data science may not be enough to …
What is ChatGPT Thinking?
Author(s): Joshua Rubin Originally published on Towards AI. Time-Travel Games and Perilous Expectations for Human-Like Tools Introduction We live in extraordinary times. OpenAI made GPT–4 [1] available to the general public via ChatGPT [2] about three weeks ago, and it’s a marvel! …
Autonomous GPT-4: From ChatGPT to AutoGPT, AgentGPT, BabyAGI, HuggingGPT, and Beyond
Author(s): Luhui Hu Originally published on Towards AI. Emerging task automation and AI agents with GPT-4 after LangChain and LlamaIndex integration trend Large Language Models on Fire (Photo courtesy by author, taken at Sedona on 4/9/2023) The emergence of ChatGPT and LLM …
Build Your Machine Learning Portfolio Using Hugging Face Spaces
Author(s): Serop Baghdadlian Originally published on Towards AI. In This Tutorial, I Will Show You How to Impress Potential Employers and Showcase Your ML Skills With Interactive Apps For FREE. Image from Huggingface Website In the highly competitive field of machine learning, …
Meta’s DINOv2: The Game-Changing Computer Vision AI Model that Doesn’t Need Fine-Tuning
Author(s): Sriram Parthasarathy Originally published on Towards AI. Building disruptive Computer Vision applications with No Fine-Tuning Imagine a world where computer vision models could learn from any set of images without relying on labels or fine-tuning. Sounds futuristic, right? Well, Meta AI …
On Common Split for Training, Validation, and Test Sets in Machine Learning
Author(s): Barak Or, PhD Originally published on Towards AI. In this post, we deal with determining the appropriate ratio for training, validation, and test sets in small and large databases Background Splitting a dataset into training, validation, and test sets is a …
On Common Split for Training, Validation, and Test Sets in Machine Learning
Author(s): Barak Or, PhD Originally published on Towards AI. In this post, we deal with determining the appropriate ratio for training, validation, and test sets in small and large databases Background Splitting a dataset into training, validation, and test sets is a …
Scale Up Bulk Similarity Calculations for Sparse Embeddings
Author(s): Rodrigo Agundez Originally published on Towards AI. ChunkDot support for sparse matrices Photo by nabil boukala on Unsplash In my previous blog post, I introduced ChunkDot, a library that performs multi-threaded matrix multiplication and cosine similarity. ChunkDot is appropriate for calculating …
Bulk Similarity Calculations for Sparse Embeddings
Author(s): Rodrigo Agundez Originally published on Towards AI. ChunkDot support for sparse matrices Photo by nabil boukala on Unsplash In my previous blog post, I introduced ChunkDot, a library that performs multi-threaded matrix multiplication and cosine similarity. ChunkDot is appropriate for calculating …
Here Are The Most Useful Built-in Python Functions For Data Science
Author(s): James Asher Originally published on Towards AI. All Functions are equal, but for data science, some are more equal than others Photo by David Clode on Unsplash With each version of Python, they introduce more built-in functions. A few you will …
How to Create a Simple and Practical API with Python and Flask
Author(s): James Asher Originally published on Towards AI. Photo by Alireza Shojaei on Unsplash Flask is my favourite Python web framework by far. It’s often described as a micro-framework for its bare-bones style — a style I really appreciate. It’s scalable and …
Introduction to GANs with TensorFlow
Author(s): Rokas Liuberskis Originally published on Towards AI. In this tutorial, we’ll cover the basics of GANs (Generative Adversarial Networks) step-by-step in TensorFlow. As an example, we’ll use a basic MNIST dataset Hello everyone! I’ll introduce you to Generative Adversarial Networks in …
This AI newsletter is all you need #43
Author(s): Towards AI Editorial Team Originally published on Towards AI. What happened this week in AI by Louie This week, the competition in the race for Generative AI and LLMs continued to intensify. Amazon announced its foray into the space by hosting …
From Science Fiction to Reality: Exploring the Potential of Generative Agents
Author(s): Sriram Parthasarathy Originally published on Towards AI. Discover How Generative Agents can Redefine Training, Entertainment, and Communication Across Sectors. Generative agents, innovative computer programs that imitate human behavior, have the remarkable ability to remember, reflect, and plan actions. These agents can …
Explore Generative AI Agents that can Remember, Reflect, and Plan Actions
Author(s): Sriram Parthasarathy Originally published on Towards AI. Discover How Generative Agents can Redefine Training, Entertainment, and Communication Across Sectors. Generative agents, innovative computer programs that imitate human behavior, have the remarkable ability to remember, reflect, and plan actions. These agents can …
Popular posts
Updates
Recent Posts
