This video we walk through a roadmap of how to get started in machine learning and AI. It can seem like a lot at first, but in this video Rob Mulla, kaggle grandmaster, breaks down his suggestions for anyone looking to start in this field. This is a good entry into anyone looking to start a career in data science or machine learning. We break it down into a few steps. This will help you map out your path to becoming a machine learning master including: which programming language to use, what courses to take, and the rest.

Timeline:
00:00 Starting your journey
00:46 Picking a programming language
02:00 Math & Statistics
03:10 Data Wrangling
03:44 Learn Algorithms
04:45 Picking a Focus
06:50 Tools
08:06 Learn through Doing (Kaggle)

Follow me on twitch for live coding streams: https://www.twitch.tv/medallionstallion_

My other videos:

Speed Up Your Pandas Code: https://www.youtube.com/watch?v=SAFmrTnEHLg
Speed up Pandas Code: https://www.youtube.com/watch?v=SAFmrTnEHLg
Intro to Pandas video: https://www.youtube.com/watch?v=_Eb0utIRdkw
Exploratory Data Analysis Video: https://www.youtube.com/watch?v=xi0vhXFPegw

Working with Audio data in Python: https://www.youtube.com/watch?v=ZqpSb5p1xQo
Efficient Pandas Dataframes: https://www.youtube.com/watch?v=u4_c2LDi4b8

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* Kaggle: https://www.kaggle.com/robikscube

#machinelearning #datascience #python

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So how do you get started with machine learning and AI? What should you learn first? Well in this video I will be discussing the exact things you need to learn to get started with machine learning. I’ll be talking about which language to learn, how much math you need and what ML algorithms to learn first.

Thanks to Kite for sponsoring this video! Download the best AI automcolplete for python programming for free: https://kite.com/download/?utm_medium=referral&utm_source=youtube&utm_campaign=techwithtim&utm_content=how-to-get-started-with-machine-learning

Enroll in The Fundamentals of Programming w/ Python
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– Tech With Tim
– Get started with Machine Learning
– Machine learning getting started
– Get started with AI

#AI #MachineLearning

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This Machine Learning basics video will help you understand what Machine Learning is, what are the types of Machine Learning – supervised, unsupervised & reinforcement learning, how Machine Learning works with simple examples, and will also explain how Machine Learning is being used in various industries. Machine learning is a core sub-area of artificial intelligence; it enables computers to get into self-learning mode without being explicitly programmed. When exposed to new data, these computer programs are enabled to learn, grow, change, and develop by themselves. So, the iterative aspect of machine learning is the ability to adapt to new data independently. This is possible as programs learn from previous computations and use “pattern recognition” to produce reliable results.

The below topics are explained in this Machine Learning basics video:
1. What is Machine Learning? ( 00:21 )
2. Types of Machine Learning ( 02:43 )
2. What is Supervised Learning? ( 02:53 )
3. What is Unsupervised Learning? ( 03:46 )
4. What is Reinforcement Learning? ( 04:37 )
5. Machine Learning applications ( 06:25 )

Subscribe to our channel for more Machine Learning Tutorials: https://www.youtube.com/user/Simplilearn?sub_confirmation=1

Download the Machine Learning Career Guide to explore and step into the exciting world of Machine Learning and follow the path toward your dream career- https://bit.ly/3eLuTUo

Watch more videos on Machine Learning: https://www.youtube.com/watch?v=7JhjINPwfYQ&list=PLEiEAq2VkUULYYgj13YHUWmRePqiu8Ddy

#MachineLearning #WhatIsMachineLearning #MachineLearningTutorial #MachineLearningBasics #MachineLearningTutorialForBeginners #Simplilearn

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Designed to boost your career as an AI and ML professional, this program showcases Caltech CTME’s excellence and IBM’s industry prowess. The artificial intelligence course covers key concepts like Statistics, Data Science with Python, Machine Learning, Deep Learning, NLP, and Reinforcement Learning through an interactive learning model with live sessions.

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Skills Covered

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– Ensemble Learning
– Computer Vision

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