📈 Predictive Modeling for Future Stock Prices in Python: A Step-by-Step Guide
The process of building a stock price prediction model using Python.
1. Import required modules
2. Obtaining historical data on stock prices
3. Selection of features.
4. Definition of features and target variable
5. Preparing data for training
6. Separation of data into training and test sets
7. Building and training the model
8. Making forecasts
9. Trading Strategy Testing
The process of building a stock price prediction model using Python.
1. Import required modules
2. Obtaining historical data on stock prices
3. Selection of features.
4. Definition of features and target variable
5. Preparing data for training
6. Separation of data into training and test sets
7. Building and training the model
8. Making forecasts
9. Trading Strategy Testing
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🏆 – AI/ML Engineer
Stage 1 – Python Basics
Stage 2 – Statistics & Probability
Stage 3 – Linear Algebra & Calculus
Stage 4 – Data Preprocessing
Stage 5 – Exploratory Data Analysis (EDA)
Stage 6 – Supervised Learning
Stage 7 – Unsupervised Learning
Stage 8 – Feature Engineering
Stage 9 – Model Evaluation & Tuning
Stage 10 – Deep Learning Basics
Stage 11 – Neural Networks & CNNs
Stage 12 – RNNs & LSTMs
Stage 13 – NLP Fundamentals
Stage 14 – Deployment (Flask, Docker)
Stage 15 – Build projects
Stage 1 – Python Basics
Stage 2 – Statistics & Probability
Stage 3 – Linear Algebra & Calculus
Stage 4 – Data Preprocessing
Stage 5 – Exploratory Data Analysis (EDA)
Stage 6 – Supervised Learning
Stage 7 – Unsupervised Learning
Stage 8 – Feature Engineering
Stage 9 – Model Evaluation & Tuning
Stage 10 – Deep Learning Basics
Stage 11 – Neural Networks & CNNs
Stage 12 – RNNs & LSTMs
Stage 13 – NLP Fundamentals
Stage 14 – Deployment (Flask, Docker)
Stage 15 – Build projects
👍19❤8
How do you start AI and ML ?
Where do you go to learn these skills? What courses are the best?
There’s no best answer🥺. Everyone’s path will be different. Some people learn better with books, others learn better through videos.
What’s more important than how you start is why you start.
Start with why.
Why do you want to learn these skills?
Do you want to make money?
Do you want to build things?
Do you want to make a difference?
Again, no right reason. All are valid in their own way.
Start with why because having a why is more important than how. Having a why means when it gets hard and it will get hard, you’ve got something to turn to. Something to remind you why you started.
Got a why? Good. Time for some hard skills.
I can only recommend what I’ve tried every week new course lauch better than others its difficult to recommend any course
You can completed courses from (in order):
Treehouse / youtube( free) - Introduction to Python
Udacity - Deep Learning & AI Nanodegree
fast.ai - Part 1and Part 2
They’re all world class. I’m a visual learner. I learn better seeing things being done/explained to me on. So all of these courses reflect that.
If you’re an absolute beginner, start with some introductory Python courses and when you’re a bit more confident, move into data science, machine learning and AI.
Join for more: https://t.me/machinelearning_deeplearning
👉Telegram Link: https://t.me/addlist/4q2PYC0pH_VjZDk5
Like for more ❤️
All the best 👍👍
Where do you go to learn these skills? What courses are the best?
There’s no best answer🥺. Everyone’s path will be different. Some people learn better with books, others learn better through videos.
What’s more important than how you start is why you start.
Start with why.
Why do you want to learn these skills?
Do you want to make money?
Do you want to build things?
Do you want to make a difference?
Again, no right reason. All are valid in their own way.
Start with why because having a why is more important than how. Having a why means when it gets hard and it will get hard, you’ve got something to turn to. Something to remind you why you started.
Got a why? Good. Time for some hard skills.
I can only recommend what I’ve tried every week new course lauch better than others its difficult to recommend any course
You can completed courses from (in order):
Treehouse / youtube( free) - Introduction to Python
Udacity - Deep Learning & AI Nanodegree
fast.ai - Part 1and Part 2
They’re all world class. I’m a visual learner. I learn better seeing things being done/explained to me on. So all of these courses reflect that.
If you’re an absolute beginner, start with some introductory Python courses and when you’re a bit more confident, move into data science, machine learning and AI.
Join for more: https://t.me/machinelearning_deeplearning
👉Telegram Link: https://t.me/addlist/4q2PYC0pH_VjZDk5
Like for more ❤️
All the best 👍👍
👍9❤5🥱1
To automate your daily tasks using ChatGPT, you can follow these steps:
1. Identify Repetitive Tasks: Make a list of tasks that you perform regularly and that can potentially be automated.
2. Create ChatGPT Scripts: Use ChatGPT to create scripts or workflows for automating these tasks. You can use the API to interact with ChatGPT programmatically.
3. Integrate with Other Tools: Integrate ChatGPT with other tools and services that you use to streamline your workflow. For example, you can connect ChatGPT with task management tools, calendar apps, or communication platforms.
4. Set up Triggers: Set up triggers that will initiate the automated tasks based on certain conditions or events. This could be a specific time of day, a keyword in a message, or any other criteria you define.
5. Test and Iterate: Test your automated workflows to ensure they work as expected. Make adjustments as needed to improve efficiency and accuracy.
6. Monitor Performance: Keep an eye on how well your automated tasks are performing and make adjustments as necessary to optimize their efficiency.
1. Identify Repetitive Tasks: Make a list of tasks that you perform regularly and that can potentially be automated.
2. Create ChatGPT Scripts: Use ChatGPT to create scripts or workflows for automating these tasks. You can use the API to interact with ChatGPT programmatically.
3. Integrate with Other Tools: Integrate ChatGPT with other tools and services that you use to streamline your workflow. For example, you can connect ChatGPT with task management tools, calendar apps, or communication platforms.
4. Set up Triggers: Set up triggers that will initiate the automated tasks based on certain conditions or events. This could be a specific time of day, a keyword in a message, or any other criteria you define.
5. Test and Iterate: Test your automated workflows to ensure they work as expected. Make adjustments as needed to improve efficiency and accuracy.
6. Monitor Performance: Keep an eye on how well your automated tasks are performing and make adjustments as necessary to optimize their efficiency.
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