Give a .NET shop vector search and chat. Work with OpenAI and local Ollama models, then bring semantic search and chat together in an EShop application. imp.i384100.net/c/6457882/12… #AD #DotNet #GenAI

Turn pretrained text embeddings into classifiers. Use TensorFlow Hub for transfer learning on real-world data, compare text classification models and visualize metrics with TensorBoard. imp.i384100.net/c/6457882/12… #AD #NLP #TensorFlow

Turn visual data into text. Work through TensorFlow and PyTorch projects covering models that combine text and images, alongside BERT, GPT and object detection. imp.i384100.net/c/6457882/12… #AD #DeepLearning #GenerativeAI

Start with Python and work toward an AI capstone. This 52-week program includes daily lessons, hands-on labs, SQL, pandas, and machine learning. trk.udemy.com/c/6457882/3227… #AD #Python #DataScience

Prepare for the AIGP exam with AI governance cases. Work through the NIST AI Risk Management Framework, model cards, and the EU AI Act while examining risks across development and deployment. imp.i384100.net/c/6457882/12… #AD #AIGovernance #AIGP

Turn movie reviews into automated analytical reports. Build a Python pipeline with Hugging Face Transformers and the Rotten Tomatoes dataset for sentiment analysis, summaries, and report generation. trk.udemy.com/c/6457882/3227… #AD #DataScience

Put transformers to work on two full NLP projects. Analyze sentiment in financial Reddit data and build an open-domain question-answering app, with frameworks including HuggingFace's Transformers. trk.udemy.com/c/6457882/3227… #AD #NLP #Python

Send this Jev prompt to any coding agent you already use. It installs Jev → audits your own workflow → finds exactly where you're burning tokens on decisions that never needed a full model → puts you ahead of 95% of people still doing this by hand. Copy it now.

Someone open-sourced a full course on AI harness engineering The free course includes 14 lectures and 8 hands-on projects teaching how to build environments that make coding agents work longer, verify themselves, and actually finish tasks. Repo: github.com/walkinglabs/learn…

You can now run Laya Decision models locally on just 4GB RAM! 🔥 Works on CPU, Mac, Windows, Linux and GPU setups. Serve Laya through a Jev-compatible API via Unsloth Desktop. GitHub: github.com/unslothai/unsloth Guide: unsloth.ai/docs/models/decis…

Give neural networks image and text tasks. Work with CNNs for image recognition and transformers for NLP, including text summarization and language translation. imp.i384100.net/c/6457882/12… #AD #DeepLearning #NLP

Start your AI portfolio with a mini project. Use low-code tools to create portfolio material, then examine technical and non-technical AI career paths. No advanced maths required. trk.udemy.com/c/6457882/3227… #AD #AI #LowCode

Build vision systems that track movement. Use OpenCV and Python for face detection, video tracking, and gesture-controlled applications, starting with image processing fundamentals. imp.i384100.net/c/6457882/12… #AD #OpenCV #ComputerVision

Build a 4-agent customer support system in n8n. Work through automated workflows, then deploy a capstone with monitoring, cost controls, and human approval checkpoints. imp.i384100.net/c/6457882/12… #AD #n8n #AIAgents

Build AI agents that analyze data. Hands-on labs and guided projects cover data pipelines, prompt engineering and RAG for knowledge-driven analytics. trk.udemy.com/c/6457882/3227… #AD #GenAI #DataAnalytics

Chatbots and image classifiers, from data to deployment. Use Keras and TensorFlow for projects in sentiment analysis, image classification, face recognition and chatbot development. imp.i384100.net/c/6457882/12… #AD #Keras #TensorFlow

Create a chatbot without writing code. Use the Amazon Bedrock console for conversational AI, text summarization and image generation, with guidance on responsible AI use. trk.udemy.com/c/6457882/3227… #AD #AmazonBedrock #GenAI

The MOST COMPLETE GUIDE for understanding LLMs from first principles is now available online to read for free Covers the model mechanics - Tokens / tokenizers - Transformers - Attention - KV cache - Prefill vs decode - Decoding controls - Model packages - Chat templates - Long context - RAG - Agents / tools - Fine-tuning - Multimodal models Then connects that to running models locally - What "local" really means - Open-weight vs opensource - Quantization - VRAM math - Hardware tiers - File formats / load safety - Runtimes / serving modes - Model selection - Privacy - Failure modes - Benchmarks - Practical setup paths You should read this, and if you cannot now then you most definitely wanna bookmark it for later Opensource & Local AI FTW

Job4Fit is worth a look - free while in beta: • CV analysis with an ATS score and what to fix • paste a job ad, get red flags, culture signals and growth outlook • mock interviews with role-specific questions and feedback on every answer job4fit.com