Hands-on Machine Learning in Python & ChatGPT

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Md Shahriar

4:44:27

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1. Setting Up Your Data Analysis Platform

1.1 Mac.pdf

1.2 Windows.pdf

1. Install Python and Jupyter Notebook.html

2.1 Instructions of setting up ChatGPT.pdf

2. Setting Up ChatGPT for Easy Machine Learning.html

2. What is Machine Learning

1. Machine Learning and Its Characteristics.mp4

03:35

2. Complete Machine Learning Work-flow.mp4

02:39

3.1 Practice datasets.zip

3. Practice datasets.html

4. Instructions for Quizzes IMPORTANT.html

3. Master Data Cleaning for Error-free ML Model

1. Load your dataset into Python environment.mp4

07:06

2. Handling missing values with Scikit-learn.mp4

12:43

3. Identify and deal with inconsistent data.mp4

11:17

4. Dealing with miss-identified data types.mp4

07:43

5. Address and remove duplicated data.mp4

04:22

6. QUIZ 1 Data Cleaning.html

7.1 data cleaning (solution).zip

7. Solution 1 Data Cleaning.html

4. Master Data Manipulation for Strong ML Model

1. Sorting and arranging dataset.mp4

05:17

2. Filter data based on conditions.mp4

10:34

3. Merging or adding of supplementary variables.mp4

03:47

4. Concatenating or adding of supplementary data.mp4

03:47

5. QUIZ 2 Data Manipulation.html

6.1 data manipulation (solution).zip

6. Solution 2 Data Manipulation.html

5. Master Data Preprocessing for Perfect ML Model

1. Feature engineering Generating new data.mp4

16:29

2. Extracting day, months, year from date variable.mp4

04:24

3. Feature encoding Assigning numeric values.mp4

05:31

4. Creating dummy variables for nominal data.mp4

07:14

5. Data standardizing and normalizing with StandardScaler.mp4

12:19

6. Splitting data into training and testing set.mp4

06:53

7. QUIZ 3 Data Preprocessing.html

8.1 data preprocessing (solution).zip

8. Solution 3 Data Preprocessing.html

6. Hands-on Machine Learning Application Part 1 Regression

1. Read It IMPORTANT.html

2. Linear regression ML model.mp4

18:18

3. Decision Tree regression ML model.mp4

08:08

4. Random Forest regression ML model.mp4

08:04

5. Support Vector regression ML model.mp4

06:26

6. XGBoost regression ML model.mp4

07:37

7. QUIZ 4 ML Model Application Part 1.html

8.1 ml model application part 1 (solution).zip

8. Solution 4 ML Model Application Part 1.html

7. Hands-on Machine Learning Application Part 2 Classification

1. Read It IMPORTANT.html

2. Logistic Regression ML model.mp4

21:44

3. Decision Tree classification ML model.mp4

13:12

4. Random Forest classification ML model.mp4

11:50

5. K Nearest Neighbours classification ML model.mp4

20:30

6. LightGBM classification ML model.mp4

13:36

7. QUIZ 5 ML Model Application Part 2.html

8.1 ml model application part 2 (solution).zip

8. Solution 5 ML Model Application Part 2.html

8. Hands-on Machine Learning Application Part 3 Clustering

1. KMeans Clustering ML model.mp4

22:05

2. Final QUIZ ML Model Application Part 3.html

3.1 fast-track ml in python & chatgpt (solution).zip

3. Final Solution Fast-Track ML in Python & ChatGPT.html

9. Tips, Tricks and Resources

1. ChatGPT Your best code companion.mp4

07:17

2.1 Complete ML workflow.pptx

2.2 ML.pptx

2. Course resources.html

Description

Hands-on Machine Learning Tutorial with Pandas, Numpy, Seaborn, Scikit-learn in Python and ChatGPT: A Complete Work-flow

What You'll Learn?

Learn to proficiently use Python for various machine learning tasks, including data cleaning, manipulation, preprocessing, and model development.
Gain expertise in building and implementing supervised machine learning models: Regressions, Random Forest, Decision Tree, SVM, XGBoost, and KNN, etc.
Acquire skills in unsupervised machine learning techniques, including KMeans for effective cluster analysis and pattern recognition.
Learn to create a streamlined and efficient workflow for building machine learning models from scratch, incorporating both Python and ChatGPT.
Develop the ability to measure and evaluate the accuracy and performance of machine learning models, enabling decisions on model selection and optimization.
Explore the integration of ChatGPT into the machine learning workflow, leveraging its capabilities for enhanced data analysis, and generating insights.
Understand strategies for selecting the most suitable machine learning model for a given task, considering factors such as accuracy, and scalability.
Apply acquired knowledge to real-world scenarios, solving diverse machine learning challenges and developing solutions.

Who is this for?

Python Enthusiasts

Data Science Aspirants

Complete Beginners

What You Need to Know?

No coding Experience is Needed.

Desktop/Laptop

More details

Description
Unlock the fast track to machine learning mastery with our comprehensive course, "Hands-on Machine Learning in Python & ChatGPT." Dive deep into hands-on tutorials utilizing essential tools like Pandas, Numpy, Seaborn, Scikit-learn, Python, and the innovative capabilities of ChatGPT.
This course is designed to guide you seamlessly through every stage of the machine learning process, ensuring a complete workflow that empowers you to tackle tasks such as data cleaning, manipulation, preprocessing, and the development of powerful supervised and unsupervised machine learning models.
In this immersive learning experience, gain proficiency in crafting supervised models, including Linear Regression, Logistic Regression, Random Forests, Decision Trees, SVM, XGBoost, and KNN. Unleash the power of unsupervised models like KMeans and DBSCAN for cluster analysis. The course is strategically structured to enable you to navigate through these complex concepts swiftly, effortlessly, and with precision.
Our primary objective is to equip you with the skills to build machine learning models from scratch, leveraging the combined strength of Python and ChatGPT. You will not only learn the theoretical foundations but also engage in practical exercises that solidify your understanding. By the end of the course, you'll have the expertise to measure the accuracy and performance of your machine learning models, enabling you to make informed decisions and select the best models for your specific use case.
Whether you are a beginner eager to enter the world of machine learning or an experienced professional looking to enhance your skill set, this course caters to all levels of expertise. Join us on this learning journey, where efficiency meets excellence, and emerge with the confidence to tackle real-world machine learning challenges head-on. Fast-track your way to becoming a proficient machine learning practitioner with our dynamic and comprehensive course.
Who this course is for:
Python Enthusiasts
Data Science Aspirants
Complete Beginners

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Introducing Shahriar: Accomplished Data Analyst and Passionate InstructorWelcome to the dynamic world of data analytics, where every byte of information holds the key to unlocking insights and shaping informed decisions. Meet Shahriar, a seasoned freelancer and a dedicated data enthusiast, who is now poised to share his wealth of knowledge and expertise as an esteemed Instructor at Udemy.With a rich tapestry of experiences spanning over three prolific years in the field, Shahriar has made an indelible mark as a Data Analyst extraordinaire. Over the course of his illustrious career, he has successfully spearheaded and completed an impressive portfolio of more than 300 projects, transcending geographical boundaries and leaving a trail of satisfied clients worldwide.Proficient in an array of cutting-edge tools and languages including Python, R, Excel, and SPSS, Shahriar's prowess extends across a spectrum of domains within the data realm. His unparalleled skills encompass data analysis, machine learning, data manipulation, data visualization, and applied statistics, to name just a few. His holistic approach to problem-solving ensures that every project is meticulously analyzed, curated, and executed to perfection, delivering results that are not just insightful but also actionable.However, what truly sets Shahriar apart is his unwavering passion for data. To him, data is more than just numbers and figures; it's a story waiting to be told. As an avid storyteller, he seamlessly weaves narratives from complex datasets, transforming raw information into compelling insights that resonate with both experts and novices. Shahriar's ability to make data relatable and engaging underscores his dedication to demystifying the world of data analytics.As he steps into his new role as an Instructor at Udemy, Shahriar is committed to sharing his wealth of knowledge with a global audience. His teaching philosophy is rooted in clarity, accessibility, and practicality. Whether you're a budding data enthusiast taking your first steps or a seasoned professional seeking to refine your skills, Shahriar's meticulously crafted courses are designed to empower and elevate your data prowess.In conclusion, Shahriar's journey from a passionate data hobbyist to a prolific freelancer and now an esteemed Udemy Instructor is a testament to his unwavering dedication, insatiable curiosity, and relentless pursuit of excellence in the realm of data analytics. Embark on this transformative learning journey with Shahriar and unravel the mysteries of data in a way that only a true storyteller can unveil. The world of data analytics awaits, and Shahriar is your guiding light.

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