04 - Deep QLearning Implementation - Part 03.zip
338 MB
04 - Deep QLearning Implementation - Part 03
❤2👍1
05 - Deep Convolutional QLearning Intuition.zip
70.2 MB
05 - Deep Convolutional QLearning Intuition
👍5❤1
06 - Deep Convolutional QLearning Implementation - Part 01.zip
326.2 MB
06 - Deep Convolutional QLearning Implementation - Part 01
👍4❤2
06 - Deep Convolutional QLearning Implementation - Part 02.zip
326.1 MB
06 - Deep Convolutional QLearning Implementation - Part 02
❤5👍2
🔅 Advanced NLP with Python for Machine Learning
🌐 Author: Gwendolyn Stripling
🔰 Level: Advanced
⏰ Duration: 1h 26m
📗 Topics: Natural Language Processing, Machine Learning, Python
📤 Join Artificial intelligence for more courses
🌀 Build upon your foundational knowledge of natural language processing by exploring more complex topics.
Please open Telegram to view this post
VIEW IN TELEGRAM
👍25❤5
This course is for anyone who wants to learn more advanced NLP methods. Instructor Gwendolyn Stripling, PhD, begins with a look at the fundamental concepts and principles of NLP, including the evolution and significance of natural language processing. She then reviews some NLP and Python basics—and introduces the NLP library spaCy—before jumping into more modern techniques and advancements in natural language processing using Transformer Models like GPT and BERT. Methods such as supervised fine-tuning, parameter efficient fine-tuning (PEFT), and retrieval-augmented generation (RAG) give you the foundational knowledge you need to improve large language model (LLM) performance. Learn the ways you can apply NLP in your applications and day-to-day, including how to analyze customer sentiments Each chapter ends with a challenge and solution, so you can test your knowledge as you go.
Please open Telegram to view this post
VIEW IN TELEGRAM
👍12❤2
Please open Telegram to view this post
VIEW IN TELEGRAM
👍17🔥1
🔅 Amplify Your Personal Brand with Generative AI
🌐 Author: Morgan Young
🔰 Level: General
⏰ Duration: 48m
📗 Topics: Personal Branding, Generative AI Tools
📤 Join Artificial intelligence for more courses
🌀 Learn how to leverage cutting-edge tools powered by generative AI to build, boost, and grow your personal brand.
Please open Telegram to view this post
VIEW IN TELEGRAM
👍19❤5
Please open Telegram to view this post
VIEW IN TELEGRAM
👍15❤3🔥1
Below is a list of guided projects to master AI & ML with Python that you should try
Please open Telegram to view this post
VIEW IN TELEGRAM
👍10❤9🔥4
Future Trends in Artificial Intelligence 👇👇
1. AI in healthcare: With the increasing demand for personalized medicine and precision healthcare, AI is expected to play a crucial role in analyzing large amounts of medical data to diagnose diseases, develop treatment plans, and predict patient outcomes.
2. AI in finance: AI-powered solutions are expected to revolutionize the financial industry by improving fraud detection, risk assessment, and customer service. Robo-advisors and algorithmic trading are also likely to become more prevalent.
3. AI in autonomous vehicles: The development of self-driving cars and other autonomous vehicles will rely heavily on AI technologies such as computer vision, natural language processing, and machine learning to navigate and make decisions in real-time.
4. AI in manufacturing: The use of AI and robotics in manufacturing processes is expected to increase efficiency, reduce errors, and enable the automation of complex tasks.
5. AI in customer service: Chatbots and virtual assistants powered by AI are anticipated to become more sophisticated, providing personalized and efficient customer support across various industries.
6. AI in agriculture: AI technologies can be used to optimize crop yields, monitor plant health, and automate farming processes, contributing to sustainable and efficient agricultural practices.
7. AI in cybersecurity: As cyber threats continue to evolve, AI-powered solutions will be crucial for detecting and responding to security breaches in real-time, as well as predicting and preventing future attacks.
1. AI in healthcare: With the increasing demand for personalized medicine and precision healthcare, AI is expected to play a crucial role in analyzing large amounts of medical data to diagnose diseases, develop treatment plans, and predict patient outcomes.
2. AI in finance: AI-powered solutions are expected to revolutionize the financial industry by improving fraud detection, risk assessment, and customer service. Robo-advisors and algorithmic trading are also likely to become more prevalent.
3. AI in autonomous vehicles: The development of self-driving cars and other autonomous vehicles will rely heavily on AI technologies such as computer vision, natural language processing, and machine learning to navigate and make decisions in real-time.
4. AI in manufacturing: The use of AI and robotics in manufacturing processes is expected to increase efficiency, reduce errors, and enable the automation of complex tasks.
5. AI in customer service: Chatbots and virtual assistants powered by AI are anticipated to become more sophisticated, providing personalized and efficient customer support across various industries.
6. AI in agriculture: AI technologies can be used to optimize crop yields, monitor plant health, and automate farming processes, contributing to sustainable and efficient agricultural practices.
7. AI in cybersecurity: As cyber threats continue to evolve, AI-powered solutions will be crucial for detecting and responding to security breaches in real-time, as well as predicting and preventing future attacks.
👍29❤11