Introduction and 2024 roadmap

0:00 this machine learning course is created for beginners who are learning in 2024 the course begins with a machine learning road map for 2024 emphasizing career paths and beginner-friendly Theory then the course moves on to Hands-On practical applications and a comprehensive end to-end project using python Todd have created this course she is an experienced data science professional her aim is to demystify machine learning Concepts making them accessible and actionable for newcomers and to bridge the gap in existing educational resources setting you on a path to success in the evolving field of machine learning looking to step into machine learning or data science it's about starting somewhere practical yet powerful in this introductory course machine learning for beginners we are going to cover the basics of machine learning and we're going to put that into practice by implementing it in a real world case study I'm d founder of Lun Tech where we are making data science and AI more accessible for individuals and businesses if you're looking for machine learning deep

1:09 learning data science or AI resources then check out the free resources section in lunch. or our YouTube channel where you can find more content and you can dive into machine learning and in AI we're going to start with machine learning road map we in this detailed section we are going to discuss the exact skill set that you need to get into machine learning we're also going to cover the definition of machine learning what is a common career path and lot of resources that you can use in order to get into machine learning then we are going to start with the actual Theory we are going to touch base the basics we're going to learn what are those different fundamentals in machine learning once we have learned the theory and we have also looked into the machine learning road map we're going to put our Theory into practice we are going to conduct an endtoend a basic yet powerful case study where we're are going to implement the linear aggression model we're going to use it both for caal analysis and for Predictive Analytics for Californian house prices we're are going to find out

2:17 the features that drive the Californian house values and we are going to discuss the stepbystep approach for conducting a real world data science project at the end of this course you are going to to know the exact machine learning road map for 2024 what are the exact skill set and the action plan that you can use to get into machine learning and in data science you are going to learn the basics when it comes to machine learning you're going to implement it into actual machine learning project end to end including implementing pandas numai psychic learn touch models medal tap and curn in Python for a real world data science project dive into machine learning with us start Simple Start strong let's get started hi there in this video we are going to talk about how you can get into machine learning in 2024 first we are going to start with all the skills that you need in order to get into machine learning step by step what are the topics that you need to cover and what are the topics that you

3:28 need to study in order to to get into machine learning we are going to talk about what is machine learning then we are going to cover step by step what are the exact topics and the skills that you need in order to become a machine learning researcher or just get into machine learning then we're going to cover the type of exact projects you can complete so examples of portfolio projects in order to put it on your resume and to start to apply for machine learning related jobs and then we are going to also talk about the type of industries that you can get into once you have all the skills and you want to get into machine learning so the exact career path and what kind of business titles are usually related to machine learning we are also going to talk about the average salary that you can expect for each of those different machine learning related positions at the end of this video you are going to know what exactly machine learning is where is it used what kind of skills are there that you need in order to get into to machine learning in 2024 and what kind of career path with what kind of compensation you can expect with the corresponding

4:37 business titles when you want to start your career in machine learning so we will first start with the definition of machine learning what machine learning is and what are the different sorts of applications of machine learning that you most likely have heard of but you didn't know that it was based on machine learning so what is machine learning machine learning is a brand of artificial intelligence of AI that helps to uh build models based on the data and then learn from this data in order to make different decisions and it's being used across different Industries uh starting from healthare till entertainment in order to improve uh the customer uh experience custom identify customer behavior um improve the sales for the businesses uh and it also helps um governments to make decisions so it's really has a wide range of applications so let's start with the healthcare for instance machine learning is being used in the healthcare to help with the uh diagnosis of diseases it can help to uh diagnose cancer uh during the co it helped many hospitals to identify whether people are getting more uh

5:49 severe side effects or they are getting p uh pneumonia um based on those pictures and that was all based on machine learning and specifically comp computer vision uh in the healthcare is also being used for drug Discovery it's being used for personalized medicine for personalizing treatment plans to improve the operations of the hospitals to understand what is the amount of uh people and uh patients that hospital can expect in each of those uh uh days per week and also to estimate the amount of doctors that need to be available the amount of uh people uh that the hospital can expect in the emergency room based on the day or the time of the day and this is basically not a machine learning application then we have uh machine learning in finance machine learning is being largely used in finance for different applications starting from fraud detection in credit cards or in other sorts of banking operations um it's also being used in trading uh with specifically in combination with quantitative Finance to help traders to make decisions with they need to go

7:00 short or long into different stocks or bonds or different assets just in general to estimate the price that those talks will happen Assets in the real time in the most accurate way uh it's also being used in uh retail uh it helps you understand an estimated demand for certain products in certain warehouses it also helps you understand what is the most appropriate or closest uh uh warehouses that the items for that corresponding customer should be shipped so it's uh optimizing the operations it's also being used to build different direct Commander systems and search engines like the famous Amazon is doing so every time when you go to Amazon and you are searching for project or product you will most likely see many article recommenders and that's based on machine learning because Amazon is uh Gathering the data and comparing your behavior So based on what you have bought based on what you are searching uh to other customers and those items to other items in order to understand what are the items that you will most likely will be interested in and eventually will buy it

8:10 and that's exactly based on machine learning and specifically different sorts of recommended system algorithm and then we have uh marketing where machine learning is being heavily used because this can help to understand uh what are these different tactics and specific targeting uh groups that that you belong and how retailers can Target you uh in order to reduce their marketing cost and to result in high conversion rates so to ensure that you buy their product then we have machine learning in autonomous vehicles that's based on machine learning and specifically uh deep learning applications uh and then we have also um uh natural language Pro processing which is highly related to the famous Chad GPT I'm sure you are using it and that's that's based on the machine learning and specifically the large language models so the Transformers large language models where you are going and providing your text and then question and the chat GPT will provide answer to you or in fact any other uh virtual assistant or chat boats those are all based on machine

9:20 learning and then we have also uh smart home devices so Alexa is based on machine learning also in agriculture uh machine learning is being used heavily these days to estimate what the weather conditions will be uh to understand what will be the uh production of different plants uh what will be the um outcome of this uh to understand and to make decisions uh also how they can optimize those uh crop uh yields to monitor uh soil health and for different sorts of applications that can just in general uh improve the uh revenue for the farmer then we have of course in the entertainment so the Vivid example is Netflix that uses the uh data uh that you are providing uh related to the movies and also based on what kind of movies you are watching Netflix is uh building this super smart recommender system to recommend you movies that you most likely will be interested in and you will also like it so in all this machine learning is being used and it's actually super powerful topic and super powerful uh field to get into and in the