Artificial Intelligence

Complete guide to train chatgpt model

Some useful AI tools in 2024 Solves anything -> Gemini Text to image -> Adobe Firefly Create AI Avatar -> HeyGen Create Art -> Midjourney Video editing -> Topview AI Text to video -> Pika 1.0 Create logo -> logodiffusion Create interface -> Uiverse Creates copycats -> Tome Essay assistant -> Jenni AI Repetitive tasks -> Zapier Copies your voice -> Eleven Labs Rewrite anything -> Quillbot Drawing assistant -> Autodraw Create slide deck -> Autodraw Write any emails -> Addy AI Summarize notes -> Wordtune Create music -> Soundraw

⚠️ WARNING!

You have been cancelled by the channel administrator.

And what if I tell you that there is such a closed telegram channel, where the guy for a percentage of profits, shares with his subscribers different private schemes to earn money? The guy has already bypassed the defence of hundreds of sites and was able to find an opportunity to earn in each of them, if you follow the actions of his instructions from the channel, you can easily make good money right now. Entry is limited and will only be available to the first 100 people who sign up ⏱👇 https://t.me/+zXMMfy8nyh05YWQ0

Unpopular opinion: ChatGPT is only as smart as the user; if garbage goes in, garbage comes out.

Breaking into ML Engineering can be very confusing in 2024! Should I learn TensorFlow or PyTorch? Python or R? Scikit-learn or XGBoost? GCP or AWS? FastAPI or Streamlit? Fundamental principles are more important than tools: - understanding statistics and deep learning is more important than TensorFlow vs PyTorch. - understanding functional and object-oriented programming is more important than Python or R. - understanding feature engineering is more important than Scikit-learn vs XGBoost. - understanding scalable and resilient architectures is more important than GCP or AWS. - understanding models serving is more important than FastAPI or Streamlit. Knowing these will allow you to pick up new emerging tools easily. Stick to fundamentals first. Join for more: https://t.me/machinelearning_deeplearning All the best 👍👍

Please take it step by step!! Me 😂

ChatGPT Prompt to learn any skill 👇👇 I am seeking to become an expert professional in [Making ChatGPT prompts perfectly]. I would like ChatGPT to provide me with a complete course on this subject, following the principles of Pareto principle and simulating the complexity, structure, duration, and quality of the information found in a college degree program at a prestigious university. The course should cover the following aspects: Course Duration: The course should be structured as a comprehensive program, spanning a duration equivalent to a full-time college degree program, typically four years. Curriculum Structure: The curriculum should be well-organized and divided into semesters or modules, progressing from beginner to advanced levels of proficiency. Each semester/module should have a logical flow and build upon the previous knowledge. Relevant and Accurate Information: The course should provide all the necessary and up-to-date information required to master the skill or knowledge area. It should cover both theoretical concepts and practical applications. Projects and Assignments: The course should include a series of hands-on projects and assignments that allow me to apply the knowledge gained. These projects should range in complexity, starting from basic exercises and gradually advancing to more challenging real-world applications. Learning Resources: ChatGPT should share a variety of learning resources, including textbooks, research papers, online tutorials, video lectures, practice exams, and any other relevant materials that can enhance the learning experience. Expert Guidance: ChatGPT should provide expert guidance throughout the course, answering questions, providing clarifications, and offering additional insights to deepen understanding. I understand that ChatGPT's responses will be generated based on the information it has been trained on and the knowledge it has up until September 2021. However, I expect the course to be as complete and accurate as possible within these limitations. Please provide the course syllabus, including a breakdown of topics to be covered in each semester/module, recommended learning resources, and any other relevant information (Tap on above text to copy)

How to Tailor Resume based on the Job Description 👇 To tailor your resume based on a job description: 1. Keyword Integration: Identify key words in the job description and incorporate them into your resume, especially in the skills and experience sections. 2. Relevant Experience: Highlight experiences that directly relate to the job requirements. Focus on accomplishments and skills relevant to the position. 3. Customize Objective or Summary: Tailor your resume objective or summary to align with the specific job, emphasizing how your skills and experience make you a strong fit. 4. Quantify Achievements: Use quantifiable metrics to showcase your achievements. Numbers stand out and provide concrete evidence of your impact. 5. Matched Skills Section: Create a skills section that mirrors the required skills in the job description. Be truthful, but emphasize the skills most relevant to the role. 6. Reorder Sections: Arrange resume sections to prioritize the most relevant information. If education is crucial, move it up; if experience is paramount, highlight it prominently. 7. Research the Company: Tailor your resume to the company culture and values. Showcase experiences that demonstrate your alignment with their mission. 8. Use Action Verbs: Start bullet points with strong action verbs to convey a sense of accomplishment and capability. Join @getjobss for latest jobs and internship opportunities Share with your friends if it helps 😄

This is a class from Harvard University: "Introduction to Data Science with Python." It's free. You should be familiar with Python to take this course. The course is for beginners. It's for those who want to build a fundamental understanding of machine learning and artificial intelligence. It covers some of these topics: • Generalization and overfitting • Model building, regularization, and evaluation • Linear and logistic regression models • k-Nearest Neighbor • Scikit-Learn, NumPy, Pandas, and Matplotlib Link: https://pll.harvard.edu/course/introduction-data-science-python

Deep Learning Course – Math and Applications 👇👇 https://www.freecodecamp.org/news/deep-learning-course-math-and-applications Best Data Science & Machine Learning Resources: https://topmate.io/coding/914624 All the best 👍👍