![Hands-On LangChain for LLM Applications Development: Documents Splitting [Part 2]](https://miro.medium.com/v2/resize:fit:700/1*GsFRA_91_VibuBd2Hl_Keg.png "Hands-On LangChain for LLM Applications Development: Documents Splitting [Part 2]")
Hands-On LangChain for LLM Applications Development: Documents Splitting [Part 2]
Author(s): Youssef Hosni Originally published on Towards AI. Once you’ve loaded documents, you’ll often want to transform them to better suit your application. The simplest example is you may want to split a long document into smaller chunks that can fit into …
A Comprehensive Guide to Data-Driven Customer Lifecycle Management
Author(s): Saif Ali Kheraj Originally published on Towards AI. Figure 1: https://www.shutterstock.com/image-vector/4-stages-customer-life-cycle-mind-2304739019 From the standpoint of data strategy, the customer lifecycle is a critical topic in the field of targeted and precise marketing. Let’s take a closer look at how it works. …
Mastering GPT-4 Code Prompts With Guardrails and Custom Instructions
Author(s): John Loewen, PhD Originally published on Towards AI. The system prompts to minimize GPT-4 Python coding frustrationDall-E 2 image: An impressionist painting of AI as a blue cube holding on to a guard rail As a Com Sci prof, I have …
7 Mistakes Beginner ML Students Make Every Year
Author(s): Boris Meinardus Originally published on Towards AI. Don’t study LLMs! You’re making a mistake! I have received a lot of DMs from people asking me for advice on how to learn machine learning. So in this post, I thought I would …
GPT-4 Custom Instructions To Optimize Python Code Creation
Author(s): John Loewen, PhD Originally published on Towards AI. Python Plotly dashboard code in less than 10 minutesDall-E 2 image: impressionist painting of prompting GPT-4 As a comp sci professor, over the past 8 months, I have heavily integrated GPT-4 into my …
Top Important Computer Vision Papers for the Week from 01/01 to 07/01
Author(s): Youssef Hosni Originally published on Towards AI. Stay Updated with Recent Computer Vision Research Every week, several top-tier academic conferences and journals showcased innovative research in computer vision, presenting exciting breakthroughs in various subfields such as image recognition, vision model optimization, …
Fast and Efficient Model Finetuning using the Unsloth Library
Author(s): Eduardo Muñoz Originally published on Towards AI. Image generated by the author on Leonardo.ai Introduction Recently a new framework or library to optimize the training and fine-tuning stage of a large language model has been released: Unsloth. This library is a …
Microsoft Phi-2: Tiny Mighty Open Source Model with Verbal Diarrhea
Author(s): Dr. Mandar Karhade, MD. PhD. Originally published on Towards AI. A new lightweight model for developing prototypes The Phi-2 model, developed by Microsoft, is a 2.7 billion-parameter language model that has recently gained attention in the field of natural language processing …
A Swift Introduction to Deep Learning with PyTorch and TensorFlow
Author(s): Günter Röhrich Originally published on Towards AI. Stepping through theory, background, and code examples Neural networks have gained incredible attention over the last decade (despite being around for much longer), and seem to have made incredible progress in the eyes of …
Categorical Encoding for Time Series: Embracing Dynamic and Meaningful Techniques
Author(s): Alexandre Warembourg Originally published on Towards AI. Let’s move beyond static encoding methods and explore dynamic, meaningful techniques for high-cardinality categorical variables.source: Image generated by Dall-E from Author prompt The categorical data type is data divided by several modalities; let’s take …
A Long-Term Demand Forecasting Model Implementation Case Study with a Major Retailer
Author(s): Alexandre Warembourg Originally published on Towards AI. Explore how I developed a core demand forecasting algorithm for ten countries, dealing with an average product sales history of 11 months and 30% new products in each batch. source : Dall-E generated picture …
How To Create Multiline Synthetic Images Using Synthtiger
Author(s): Eivind Kjosbakken Originally published on Towards AI. Making synthetic data is one of the quickest ways of acquiring a labeled dataset for supervised learning. Instead of labeling files yourself, you already have the ground truth as you are creating the images. …
How To Analyze Data Like a Pro Without Coding?
Author(s): Shreepada Rao Originally published on Towards AI. Leveraging Databricks assistant and Copilot for your day-to-day tasks to boost productivityImage by author: Databricks Assistant “With our new copilot for work, we’re giving people more agency and making technology more accessible through the …
How to Train a Custom Faster RCNN Model In PyTorch
Author(s): Dr. Leon Eversberg Originally published on Towards AI. Fine-tuning a pre-trained Faster RCNN model with custom images in the COCO data format using PyTorchTraining and validation loss during model training. Source: Author In this PyTorch tutorial for beginners, we will use …
Practical Nuances of Time Series Forecasting — Part II— Improving Forecast Accuracy
Author(s): Santoshkumarpuvvada Originally published on Towards AI. Practical Nuances of Time Series Forecasting — Part II— Improving Forecast Accuracy In continuation of enhancing our understanding of time series forecasting, let’s get started with part 2. (Check out the part 1 here). Many …
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