Data Science, Machine Learning, AI & IOT

02 June 2026 10:10

🔬 AI Research Digest
📅 Week of May 27–Jun 2, 2026
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1. 📱 MobileGym: Verifiable & Parallel Mobile GUI Agent Simulation
Authors/Org: Chinese Academy of Sciences, Peking University, CUHK | arXiv: 2605.26114
Bottleneck solved: Training mobile GUI agents at scale is blocked by slow, non-deterministic simulators with no reliable reward signal.
MobileGym runs 256 parallel Android instances in-browser, uses JSON state for bit-exact reproducibility, and ships 416 task templates with sub-millisecond judges — lifting Qwen3-VL-4B real-device pass rate from 32% → 73% with GRPO fine-tuning on a single 3×RTX node.
🔗 arXiv 2605.26114

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2. 🦞 AutoResearchClaw: Self-Reinforcing Autonomous Research with Human-AI Collaboration
Authors/Org: Aiming Lab | arXiv: 2605.20025
Bottleneck solved: Fully autonomous research pipelines hallucinate results and lack a principled way to incorporate human oversight without defeating the purpose of automation.
AutoResearchClaw combines structured multi-agent debate, a self-healing executor with Pivot/Refine loops, and seven human-in-the-loop intervention modes — outperforming AI Scientist v2 by 54.7% on ARC-Bench while preventing fabricated citations via live literature grounding.
🔗 arXiv 2605.20025

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3. 🧠 nanochat: Full-Stack LLM Training Pipeline for ~$100
Authors/Org: Andrej Karpathy | GitHub: karpathy/nanochat
Bottleneck solved: End-to-end LLM training (pretraining → RLHF → chat UI) has no minimal, hackable reference implementation that a single developer can run affordably.
Unlike nanoGPT which stops at pretraining, nanochat covers tokenization, SFT, evaluation, inference, and a ChatGPT-like UI in one dependency-minimal codebase — reaching GPT-2 capability in ~$48 of cloud GPU time.
🔗 github.com/karpathy/nanochat

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💡 Stay curious. Read the papers.

For More: @kdnuggets @datasciencechats

Data Science, Machine Learning, AI & IOT

31 May 2026 10:46

🤖 AI & Data Science Weekly Digest
📅 Week of May 25–May 31, 2026
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1. ⚡ Google Launches Gemini 3.5 Flash at I/O 2026
Google released Gemini 3.5 Flash — a frontier model that's 4x faster than comparable models and optimized for agentic workflows, coding, and multimodal tasks. Developers can access it via the Gemini API with 1M token context at $1.50/$9 per 1M tokens, and the new Managed Agents feature lets a single API call spin up a full reasoning agent with tool use and code execution.
🔗 Google Introduces Gemini 3.5 Flash at I/O 2026

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2. 📢 OpenAI Opens ChatGPT Ad Platform to All Businesses
OpenAI launched a self-serve Ads Manager at ads.openai.com, eliminating the previous $50,000 minimum spend and introducing CPC bidding, a Conversions API, and pixel-based tracking. This shifts ChatGPT from a subscription-only product toward a major ad-supported platform — opening new acquisition channels for data teams and developer-focused SaaS companies.
🔗 OpenAI launches self-serve ad platform

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3. 🧬 PolyU Researchers Store Data in Engineered Proteins
The Hong Kong Polytechnic University pioneered a method to store and retrieve digital data using de novo designed unnatural proteins, offering a radically denser and more stable storage medium as AI-generated data volumes explode. For data teams, this signals a new frontier in long-term archival storage that could complement or eventually compete with DNA and tape-based cold storage.
🔗 Data explosion in AI era: PolyU leads breakthroughs in protein-based data storage

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4. 💡 Light-Based Computing Could Slash AI Energy Costs
Penn researchers created a hybrid light-matter particle (polariton) system that dramatically accelerates AI inference while consuming far less energy than silicon-based hardware. This matters for data teams running large-scale model inference, where energy cost and latency are growing operational constraints.
🔗 Breakthroughs in AI Innovations for May 2026

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5. 🛡️ Five Nations Release Agentic AI Security Guidance
Cybersecurity agencies from the US, UK, Australia, Canada, and New Zealand jointly published guidance on "Careful Adoption of Agentic AI Services," covering risks like prompt injection, over-permissioned agents, and supply chain attacks. Software teams deploying AI agents in production should treat this as a practical security checklist before rollout.
🔗 7 Explosive AI Updates in May 2026

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💡 Stay ahead. Stay curious.

For More: @kdnuggets @datasciencechats

Data Science, Machine Learning, AI & IOT

30 May 2026 18:48

🤖 AI & Data Science Weekly Digest
Week of May 26–30, 2026

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1. 🔍 Google Gemini 3.5 Flash Goes Global at Google I/O
Google launched Gemini 3.5 Flash as the new default model for AI Search Mode — flagship-level intelligence at fast-inference speeds, now live in 200 countries across 98 languages, free with no subscription.

2. 🧠 Google Gemma 4 — Open Model, Closed-Model Performance
Gemma 4's 26B Mixture-of-Experts model activates only 3.8B parameters at inference time, outperforming models 20x its size on reasoning and agentic benchmarks.

3. 🗣️ xAI Drops Grok 4.3 with Voice Cloning & Agentic Modes
xAI released Grok 4.3 at aggressively low pricing, featuring a voice cloning suite and a dedicated Imagine creative agent mode for multimodal projects.

4. 💳 Ant Group Launches Agentic Commerce Trust Protocol
Alipay's parent company unveiled a full-stack AI payments infrastructure — including an AI Wallet and a Trust Protocol governing transactions executed autonomously by AI agents.

5. ⚠️ First Large-Scale Study Exposes Bias in Hiring Algorithms
Researchers published the first empirical large-scale study of hiring algorithms in the wild, uncovering systematic and concerning candidate rejection patterns across production systems.

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💡 Stay ahead. Stay curious.

For More: @kdnuggets @datasciencechats

Data Science, Machine Learning, AI & IOT

07 January 2026 07:22

🚀 Popular YouTube Channels to Learn AI & ML 🤖📚
Whether you’re a beginner or going deep into research, these channels are gold for AI/ML learning 👇
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#AI #MachineLearning #DeepLearning #DataScience #LearningResources

Data Science, Machine Learning, AI & IOT

10 November 2025 13:45

5-Day AI Agents Intensive Course with Google

⏰ Nov 10 onwards

#agents #freecourse

https://www.kaggle.com/learn-guide/5-day-agents

Data Science, Machine Learning, AI & IOT

08 August 2025 04:04

🚀 Introducing GPT-5: Launched 32 months after ChatGPT, GPT-5 is hailed as a "major upgrade" and a "significant step along the path to AGI." It's described as conversing with a "PhD level expert" across any field, a substantial leap from previous models.

📈 Unprecedented Growth & Impact: ChatGPT now boasts 700 million weekly users, relying on it for work, learning, advice, and creation. GPT-5 aims to be intuitive, useful, smart, and fast.

💡 Enhanced Reasoning and Capabilities: GPT-5 incorporates a "reasoning paradigm" allowing it to "pause to think" for more intelligent, precise answers, eliminating the trade-off between speed and thoughtfulness. It can write entire computer programs, plan events, and explain complex health information.

📊 Superior Performance Metrics:

Coding: Sets new highs on SWEBench (real software engineering tasks) and Aider Polyglot (multilingual programming).

Reasoning: Outperforms previous models and most human experts on MMMU (multimodal reasoning) and AIME (mathematical reasoning).

Reliability: Significantly reduces hallucinations, making it the "most reliable, most factual model ever," and performs exceptionally well on health-related questions.


🌐 Broad Accessibility & Tiered Access: GPT-5 is rolling out immediately, available to free, Plus, Pro, NT, Enterprise, and EDU users. Free users get GPT-5 initially before transitioning to Mini, while paid tiers receive higher or unlimited usage with extended thinking capabilities.

🛠️ Powerful Integrations & Personalization: All existing ChatGPT tools (search, file/image upload, data analysis, image generation, memory, custom instructions) work seamlessly with GPT-5. New features include customizable chat colors, experimental "personalities" (supportive, sarcastic), and crucial integrations with Gmail and Google Calendar for enhanced scheduling and personal assistance.

🛡️ Advanced Safety Features: OpenAI has overhauled safety training with "safe completion," which aims to maximize helpfulness within safety constraints, offering partial answers or alternatives instead of outright refusals. GPT-5 is also significantly less deceptive.

🧪 Recursive Model Improvement: New training techniques involve using AI itself to generate high-quality synthetic data and curriculum, creating a "recursive improvement loop" where older models enhance the training data for newer generations.

⚕️ Transformative Healthcare Application: Highlighted as a top use case, GPT-5 is the "best model ever for health," scoring highly on the HelpBench evaluation. A personal testimony demonstrated its ability to translate complex medical reports into plain language, aid in critical decision-making, and empower patients.

💻 Revolutionizing Coding: GPT-5 is proclaimed the "best coding model in the world," excelling at "Agentic coding tasks" where it can autonomously tackle complex problems, build entire web apps (like a French learning app or a finance dashboard), and even fix its own code. It also exhibits a strong sense of aesthetics in front-end development.

🤝 Developer Focus & API Enhancements: Available in API today (GPT-5, Mini, Nano), with tiered pricing. New API features include a "reasoning effort" parameter for latency control, "Custom Tools" for flexible tool calls, "Tool Call Preambles" for explanations, and a "Verbosity programmer" for output control. The context window has doubled to 400K tokens.

🏢 Enterprise & Government Adoption: Over 5 million businesses already use OpenAI technology, with GPT-5 expected to be a "step function" in enabling industries like life sciences (Amgen), finance (BBVA), and healthcare (Oscar Health). Two million US federal employees will also gain access to GPT-5 and ChatGPT.

@kdnuggets @datasciencechats

Data Science, Machine Learning, AI & IOT

16 April 2025 11:34

https://cloud.google.com/blog/products/application-development/firebase-studio-lets-you-build-full-stack-ai-apps-with-gemini
#ai

@kdnuggets @datasciencechats

Data Science, Machine Learning, AI & IOT

27 December 2024 08:55

Did you know we have some unique learning posts on our WhatsApp channel that doesnt get shared here? Follow our whatsapp channel to keep up with those updates. (Your contact numbers stay anonymous on whatsapp channels)
https://bit.ly/dsnwhatsapp

Data Science, Machine Learning, AI & IOT

19 December 2024 17:40

Google announced Gemini 2.0, a more advanced AI model capable of native image and audio output and tool use. This new model powers several projects, including Project Astra (a universal AI assistant) and Project Mariner (browser-based task completion). Gemini 2.0 Flash, an experimental version, is available to developers, with wider release planned. Google emphasizes responsible AI development, prioritizing safety and security in its applications. The announcement highlights Gemini 2.0's integration into Google products and its potential to revolutionize user experience
https://blog.google/technology/google-deepmind/google-gemini-ai-update-december-2024/
#gemini
@kdnuggets @datasciencechats

Data Science, Machine Learning, AI & IOT

14 November 2024 17:02

Those who missed to register the course. You can find all the content of course:
@kdnuggets @coursenuggets
https://www.youtube.com/playlist?list=PLqFaTIg4myu-b1PlxitQdY0UYIbys-2es

Data Science, Machine Learning, AI & IOT

09 November 2024 05:32

Our channel is now on whatsapp too.

Feel free to join. We will be sharing some exclusive content posts on whatsapp and linkedin. So dont miss out.
Whatsapp:🔗
https://whatsapp.com/channel/0029Vaw8loEIXnlogBO5ma1H
Linkedin:🔗
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Data Science, Machine Learning, AI & IOT

25 October 2024 04:41

Join the FREE 5-Day 🤖 Gen AI Intensive Course with Google

Join @coursenuggets for more
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Data Science, Machine Learning, AI & IOT

14 August 2024 08:42

📣Hurry Up 50% sitewide special discount lasting only few hours on one of the leading online learning platforms 📣

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Data Science, Machine Learning, AI & IOT

15 June 2024 16:55

If you are a fresher important to realise how important data structures and algorithms are in your preparation to get into software journey. Here is a well documented roadmap that you could use with any programming language. If you are looking to expand into datascience then via python 🐍
#beginner #datastructure #python #fresher

Feel free to discuss on practising this in our exclusive python chats channel
https://t.me/joinchat/BNEH6lWLXAYvblVPWbb_ag

@kdnuggets @datasciencechats

Data Science, Machine Learning, AI & IOT

29 February 2024 06:20

https://www.kdnuggets.com/collection-of-free-courses-to-learn-data-science-data-engineering-machine-learning-mlops-and-llmops
#freecourses
@kdnuggets @datasciencechats

Data Science, Machine Learning, AI & IOT

01 June 2026 10:10

🤖 AI & Data Science Weekly Digest
📅 Week of May 26–June 1, 2026
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1. 🧠 Anthropic Releases Claude Opus 4.8 with Faster, Cheaper Inference
Anthropic launched Claude Opus 4.8, featuring stronger benchmarks, improved honesty, dynamic workflows in Claude Code, and a fast mode that runs at 2.5× the speed of previous models at one-third the cost. Data and engineering teams get a meaningfully cheaper path to high-capability agentic workflows without sacrificing quality.
🔗 Anthropic Release Notes – May 2026

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2. 🔧 Anthropic Acquires Stainless, the Dev-Tools Startup Behind OpenAI and Google SDKs
Anthropic acquired Stainless, whose tooling auto-generates idiomatic SDKs and is already used by OpenAI, Google, and Cloudflare to ship client libraries. This gives Anthropic direct control over the developer experience layer, signaling a deeper push to own the full API toolchain.
🔗 Anthropic has acquired the dev tools startup used by OpenAI, Google, and Cloudflare – TechCrunch

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3. 🤖 Claude Managed Agents Now Support Private MCP Servers and Custom Sandboxes
Anthropic's Claude Managed Agents can now run inside a developer-controlled sandbox while connecting to private Model Context Protocol (MCP) servers, with the agent loop remaining on Anthropic's infrastructure. This hybrid architecture lets teams integrate proprietary data and tools into production agents without exposing sensitive resources externally.
🔗 Google IO 2026 and Anthropic advance agentic AI for businesses

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4. ⚡ AMD EPYC "Venice" Enters Production on TSMC 2nm — First HPC Chip at This Node
AMD began production ramp of its 6th Gen EPYC "Venice" processor on TSMC's 2nm process, making it the first high-performance computing product at this fabrication node. Better performance-per-watt and higher transistor density directly benefit data center operators running AI inference and large-scale data pipelines under tight power budgets.
🔗 AMD Announces Production Ramp of Next-Generation AMD EPYC Processor "Venice" on TSMC 2nm

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5. 💻 OpenAI Codex Reaches 4 Million Active Users Powered by GPT-5.5
OpenAI's Codex coding agent, now running on GPT-5.5, has hit 4 million active users — reflecting rapid enterprise adoption of AI-assisted software development. For developer and data teams, this signals that agentic coding tools are moving from novelty to standard workflow infrastructure.
🔗 btibor91/openai-and-anthropic-news-from-the-past-week-week-20-2026-c7d3d5a42546">OpenAI and Anthropic news from the past week (Week 20, 2026)

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💡 Stay ahead. Stay curious.

For More: @kdnuggets @datasciencechats

Data Science, Machine Learning, AI & IOT

31 May 2026 05:40

🔬 *AI Research Digest*
📅 Week of May 24–May 30, 2026
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**1. 🤖 OpenClaw-RL — Train Any RL Agent Simply by Talking**
**Authors:** Gen-Verse (open-source org) | **arXiv:** 2603.10165
**Bottleneck solved:** Eliminates the need for manually defined reward functions in RL fine-tuning by intercepting live multi-turn conversations and using next-state signals as universal training feedback. Developers running self-hosted models via OpenClaw can now continuously fine-tune a personalized agent in the background — across terminal, GUI, SWE, and tool-call settings — without interrupting usage or writing a single reward function.
🔗 [OpenClaw-RL: Train Any Agent Simply by Talking](https://arxiv.org/abs/2603.10165)

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**2. 💰 Beyond the Context Window — Memory vs. Long-Context LLMs for Agents**
**Authors:** Independent researchers | **arXiv:** 2603.04814
**Bottleneck solved:** Quantifies the cost-performance tradeoff between stuffing full conversation history into long-context LLMs versus maintaining a structured fact-based memory store — directly addressing the spiraling inference cost of persistent agents. Data and ML teams building production agentic systems can use this analysis to decide when a RAG-style memory layer is cheaper and more accurate than paying per-token for a 1M-context window.
🔗 [Beyond the Context Window — arXiv](https://arxiv.org/abs/2603.04814)

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**3. ⚡ The 1/W Law — Context-Length Routing Beats GPU Upgrades for LLM Efficiency**
**Authors:** Infrastructure/systems researchers | **arXiv:** 2603.17280
**Bottleneck solved:** Shows that routing short and long context requests to separate GPU pools (two-pool topology) delivers ~2.5× better tokens-per-watt than a homogeneous H100 fleet — more gain than upgrading to B200s (~1.7×) — meaning smarter routing architecture is a bigger energy and cost lever than hardware. For teams running LLM inference at scale, this paper provides an analytical blueprint to cut infrastructure costs without waiting for the next chip generation.
🔗 [The 1/W Law — arXiv](https://arxiv.org/abs/2603.17280)

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💡 *Stay curious. Read the papers.*

For More: @kdnuggets @datasciencechats

Data Science, Machine Learning, AI & IOT

25 April 2026 17:16

Brief Summary:
OpenAI officially released GPT-5.5 on April 23, 2026, transitioning from a chat assistant to a fully "agentic" system.

Here are the 5 key updates:
Agentic Workflows: Autonomously handles multi-step tasks across browsers and software with self-correction.
SOTA Reasoning: Achieves 82.7% on Terminal-Bench 2.0, significantly outperforming Claude 4.7 and Gemini 3.1.
1M Token Context: Vastly improved reliability for processing massive codebases and long-form legal archives.
Thinking & Pro Tiers: New specialized versions optimized for deep reasoning and high-stakes enterprise work.
Enhanced Efficiency: Delivers smarter performance at GPT-5.4 speeds while consuming fewer tokens per task.

@kdnuggets @datasciencechats
https://openai.com/index/introducing-gpt-5-5/

Data Science, Machine Learning, AI & IOT

27 December 2025 12:13

Google is expanding the Gemini 3 model family with the release of Gemini 3 Flash, which offers frontier intelligence built for speed at a fraction of the cost

@kdnuggets @datasciencechats
Read More: https://blog.google/products/gemini/gemini-3-flash

Data Science, Machine Learning, AI & IOT

27 August 2025 10:19

Here are latest Gemini image editing features:
🎨 Maintaining Likeness: Photos of people and pets consistently look like themselves even when you change their hairstyle or outfit.

📍 Change Scenarios: Place a person or pet in new locations or give them a new look while keeping their original appearance.

🔄 Blend Photos: Combine multiple photos to create a new scene—like you and your dog on a basketball court!

✏️ Multi-turn Editing: Continuously edit an image. Start with an empty room, paint the walls, then add furniture.

✨ Mix Designs: Apply the style or texture from one image to an object in another—like putting a butterfly's wing pattern on a dress.

Read More: https://blog.google/intl/en-mena/product-updates/explore-get-answers/nano-banana-image-editing-in-gemini-just-got-a-major-upgrade/
@kdnuggets @datasciencechats

Data Science, Machine Learning, AI & IOT

01 August 2025 10:22

https://developers.googleblog.com/en/introducing-opal/
@kdnuggets @datasciencechats

Data Science, Machine Learning, AI & IOT

06 January 2025 18:40

Building LLMs - Stanford Course
#ai #generativeai #llm

https://www.youtube.com/watch?v=9vM4p9NN0Ts

@kdnuggets @datasciencechats

00:10 Building Large Language Models overview
02:21 Focus on data evaluation and systems in industry over architecture
06:25 Auto regressive language models predict the next word in a sentence.
08:26 Tokenizing text is crucial for language models
12:38 Training a large language model involves using a large corpus of text.
14:49 Tokenization process considerations
18:40 Tokenization improvement in GPT 4 for code understanding
20:31 Perplexity measures model hesitation between tokens
24:18 Comparing outputs and model prompting
26:15 Evaluation of language models can yield different results
30:15 Challenges in training large language models
32:06 Challenges in building large language models
35:57 Collecting real-world data is crucial for large language models
37:53 Challenges in building large language models
41:38 Scaling laws predict performance improvement with more data and larger models
43:33 Relationship between data, parameters, and compute
47:21 Importance of scaling laws in model performance
49:12 Quality of data matters more than architecture and losses in scaling laws
52:54 Inference for large language models is very expensive
54:54 Training large language models is costly
59:12 Post training aligns language models for AI assistant use
1:01:05 Supervised fine-tuning for large language models
1:04:50 Leveraging large language models for data generation and synthesis
1:06:49 Balancing data generation and human input for effective learning
1:10:23 Limitations of human abilities in generating large language models
1:12:12 Training language models to maximize human preference instead of cloning human behaviors.
1:16:06 Training reward model using softmax logits for human preferences.
1:18:02 Modeling optimization and challenges in large language models (LLMs)
1:21:49 Reinforcement learning models and potential benefits
1:23:44 Challenges with using humans for data annotation
1:27:21 LLMs are cost-effective and have better agreement with humans than humans themselves
1:29:12 Perplexity is not calibrated for large language models
1:33:00 Variance in performance of GPT-4 based on prompt specificity
1:34:51 Pre-training data plays a vital role in model initialization
1:38:32 Utilize GPUs efficiently with matrix multiplication
1:40:21 Utilizing 16 bits for faster training in deep learning
1:44:08 Building Large Language Models from scratch

Data Science, Machine Learning, AI & IOT

26 December 2024 10:27

https://blog.google/products/google-cloud/ai-trends-business-2025/
@kdnuggets @datasciencechats
#AINews #Google

Data Science, Machine Learning, AI & IOT

18 November 2024 14:29

Differences between RAG, Agents and Agentic RAG
@kdnuggets @datasciencechats

Subscribe to WhatsApp channel for the post
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Data Science, Machine Learning, AI & IOT

14 November 2024 16:05

Who all are participating here? If you havent there is still time to participate and get trained for free. Highly recommend if you want to learn genai in short span of time. Are you doing? Comment below.

Data Science, Machine Learning, AI & IOT

06 November 2024 14:34

The AI for Impact Hackathon, presented by Google Cloud and powered by Hack2skill, is a unique opportunity to leverage the transformative power of AI to address pressing social challenges across the APAC region.
You can participate in the hackathon for free with below link.

Deadline: 17th Nov

Register : https://bit.ly/4hEcMQI

Data Science, Machine Learning, AI & IOT

13 October 2024 16:15

AI Python for beginners Free course for limited period by Andrew Ng
#ai #python
Join @coursenuggets for more
@kdnuggets @datasciencechats

https://www.deeplearning.ai/short-courses/ai-python-for-beginners/

Data Science, Machine Learning, AI & IOT

30 July 2024 08:19

Did you know we have a linkedin community where useful datascience related posts are shared frequently?

If you havent joined yet please join
https://www.linkedin.com/groups/13661437/

Data Science, Machine Learning, AI & IOT

04 April 2024 08:11

https://www.youtube.com/watch?v=wjZofJX0v4M
@kdnuggets @datasciencechats

Data Science, Machine Learning, AI & IOT

13 February 2024 07:00

Marketing strategy and AI-Free Webinar from Google

In this session you will learn:

How is AI changing the marketing landscape and what are the opportunities for marketers

AI-powered marketing tools you can try

Supercharging your digital marketing strategy

https://bit.ly/googleaimarketing

#ai #freecourse #marketing
@kdnuggets @datasciencechats @coursenuggets