Harshit Harsh’s Post

Everyone wants to learn AI… but most people are starting the wrong way. They jump into Machine Learning without understanding Python. They try to build models without knowing Data Science basics. That’s why they get stuck. The truth is simple: 👉 Start with Python 👉 Move to Data Science 👉 Then Machine Learning 👉 Then build real projects Don’t rush the process. Build step by step. 💬 Where are you in this journey? #Python #DataScience #AI #MachineLearning #LearnToCode #Tech

Python for Machine Learning — Part 2 Same data… different speed 👀 That’s NumPy. Python lists store values. NumPy arrays compute on them 🧠 Which means: Faster calculations Less memory usage Better performance at scale That’s why every ML workflow starts here. This isn’t optional. It’s foundational. Follow Harshit Harsh for the full series 🚀 Repost to help someone learn NumPy right. #Python #NumPy #MachineLearning #DataScience #AI #MLBasics #LearnToCode #dataxplain

Most people think AI is complicated. But here’s something simple I built in Python 👇 I trained a model that can recognize human emotions from images No huge team. No expensive setup. Just Python + curiosity. What surprised me most? 👉 Even a simple model can give powerful results. This made me realize: You don’t need to be an expert to start building AI. You just need to start. What’s something cool you’ve built recently? 👇 #Python #MachineLearning #AI #Coding #LearningInPublic

When I started learning Python back in 2022, I had a feeling this language was going to grow much bigger. At that time, I didn’t fully realize how important it would become. Now in 2026, we are clearly living in the era of AI, Machine Learning, and automation — and almost everything is connected to Python in some way. If you want to enter these fields, Python is no longer optional, it’s essential. Looking back, starting with Python was one of the best decisions I made. So if you’re still confused about where to begin, don’t waste time jumping between languages. Start with Python, stay consistent, and it will take you to the next level 🚀

Here’s a complete Pandas cheat sheet covering essential to advanced commands. Perfect for quick revision 🚀 #DataScience #Pandas #Python #DataAnalysis #MachineLearning #AI #Learning #CareerGrowth

Carousel: Slide 1: 'Two languages. Different purposes. Both essential for AI in 2026.' Slide 2: Python — What it's best for in AI Slide 3: TypeScript — What it's best for in AI Slide 4: When to use which Slide 5: 'You don't have to choose. Learn both — here's where to start.' #TypeScript #Python #AI #AIBeginners #LearningInPublic #PakistanTech

“InsightFace Explained: From Images to Embeddings in Python Using Deep Learning” Most tutorials focus on how to use a library. In this article, I focused on something more important: 👉 Understanding how InsightFace works under the hood 👉 How images are converted into embeddings 👉 How face matching actually works 👉 And how to build a simple, production-style pipeline using Django I’ve broken everything down step by step—from uploading a selfie to retrieving matching photos from a database. If you’re working with: Computer Vision Machine Learning Python backend systems Or building real-world AI applications this might be useful for you. Would love your feedback 👇 Here is the link to read my article https://lnkd.in/gARtC9Ng #ArtificialIntelligence #MachineLearning #ComputerVision #Python #DeepLearning

Today, I focused on understanding data types in Python. I learned about different types of data such as strings, integers, floats, and boolean values. I also explored how to check the type of a variable using the type() function. This helped me understand how Python handles different kinds of data internally. One important lesson today was that mixing data types incorrectly can cause errors, and proper conversion is necessary when working with numbers and text. Building a strong foundation step by step is helping me gain confidence in Python and preparing me for future topics in Data Science and Machine Learning. #Day3 #Python #DataTypes #LearningJourney #DataScience #AI #Consistency

🚀 Day 20 of My Generative & Agentic AI Journey! Today’s focus was on exploring Built-in Functions in Python — powerful tools that make coding easier and more efficient. Here’s what I learned: 🛠️ Built-in Attributes: • name → Tells the name of the current module • doc → Used to access the documentation of a function ⚙️ Built-in Functions: • filter() → Filters elements based on a condition • len() → Returns the length of a collection • type() → Identifies the data type • sum() → Adds elements of a collection • max() / min() → Finds the largest and smallest values 💡 Key takeaway: Built-in functions help reduce code complexity and improve efficiency, making Python more powerful and developer-friendly. Continuing to explore more of Python’s capabilities 🚀 #Day20 #Python #GenerativeAI #AgenticAI #LearningJourney #BuildInPublic