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Machine learning relies heavily on mathematical foundations. #tech #ml #explore #fyp #ai

FREE Data Analytics learning resources. Seriously, start here before paying for any courses. These are FREE & a great introduction for any skill you want to learn. - SQL: https://www.youtube.com/watch?v=7S_tz1z_5bA - Excel: https://www.youtube.com/watch?v=pCJ15nGFgVg - Tableau: https://www.youtube.com/watch?v=aHaOIvR00So - Python: https://www.youtube.com/watch?v=LHBE6Q9XlzI #dataanalytics #dataanalyst #datascience #womenintech #aiengineering #techcareers

Comment “project” for my full video that breaks each of these projects down in detail with examples from my own work. If you’re using the Titanic, Iris, or COVID-19 dataset for data analytics projects, STOP NOW! These are so boring and over used and scream “newbie”. You can find way more interesting datasets for FREE on public data sites and you can even make your own using ChatGPT or Claude! Here are the 3 types of projects you need: ↳Exploratory Data Analysis (EDA): Exploring a dataset to uncover insights through descriptive statistics (averages, ranges, distributions) and data visualization, including analyzing relationships between variables ↳Full Stack Data Analytics Project: An end-to-end project that covers the entire data pipeline: wrangling data from a database, cleaning and transforming it. It demonstrates proficiency across multiple tools, not just one. ↳Funnel Analysis: Tracking users or items move from point A to point B, and how many make it through each step in between. This demonstrates a deeper level of business thinking by analyzing the process from beginning to end and providing actionable recommendations to improve it Save this video for later + send to a data friend!

Here’s your full roadmap on how to get into machine learning. Comment “Roadmap” to get the pdf. Save and follow for more. #ai #machinelearning #coding #programming #cs

Let’s build a Machine Learning Model for Sentiment Analysis! 🤖💬 Using this dataset that I found online, I was able to experiment with building ML Models using Tensorflow and Python. 💻 This is the first time I’ve made a video about building an ML Model, so let me know if you’d like to see more! 🎥 After testing this, I was pretty impressed with the results. Would you like to see that video? 👀

I won’t be mad if you copy this entire roadmap… #dataanalyst #dataanalysis #dataanalytics #data #analyst #techjobs #breakintotech #wfh #workfromhome #wfhjobs #remotejobs #remotework #excel #sql #tableau #python

Repost to share with friends ♻️ Here’s how to become a data analyst in 2026 and beyond? 📈 The original video was 5 minutes long and I had to cut it down to 3 minutes because instagram. One part that got cut off was the job market. Should I post a part 2? what are other skills that would you add to the list?? #dataanalysis #dataanalyst #sql #python

These are some of the best beginner-friendly resources I’ve found to actually understand machine learning. Nothing overly complicated, just what you need to get the concepts and start building. Comment ML and I’ll send you all the resources.

2025 machine learning roadmap - it’s time to start prepping for AI’s takeover 💡🤖 resources mentioned: VIDEO: Full Applied AI Lectures by Cassie Kozyrkov Neural Networks: Zero to Hero by Andrej Karpathy Machine Learning Specialization by Andrew Ng BOOKS: An Introduction to Statistical Learning Mathematics for Machine Learninf Artificial Intelligence: A Modern Approach FOR PRACTICE: Machine Learning with PyTorch and Scikit-Learn AIML.com . . #machinelearning #ai #resources #tech #programming #womenintech #coder #programacao #latinasintech #swe

watch this if you want to become a data analyst in 2026, these are my top simple tips 📊 1. Learn SQL: its the tool you’ll use to get data from databases, and then use to analyse business performance 2. Learn Excel or something similar: it’s great for ad hoc analysis and building engaging charts and diagrams 3. Get familiar with a reporting tool, you don’t need to be great at this just an understanding is fine 4. The core skills are communicating your insights clearly and understanding business metrics Save this and come back to it when you’re planning what to learn, I have links on my profile for courses/guides for each of these aspects!

1. Look at the big picture. 2. Get the data. 3. Explore and visualize the data to gain insights. 4. Prepare the data for machine learning algorithms. 5,. Select a model and train it. 6. Fine-tune your model. 7. Present your solution. 8. Launch, monitor, and maintain your systen. The Unbelievable Perks Exclusive Instagram Subscribers🔻 ➡️ Resume review & ATS Editable Resume Template ➡️ Priority replys ➡️ Exclusive QA ➡️ Job Postings ➡️ MIT + Stanford notes ➡️ Data Science Masterclass PDF Notes ⭐️ And many more just for Rs.45/month #datascience #machinelearning #python #ai #dataanalytics #artificialintelligence #deeplearning #bigdata #agenticai #aiagents #statistics #dataanalysis #datavisualization #analytics #datascientist #neuralnetworks #100daysofcode #genai #llms #datasciencebootcamp

Comment ‘Projects’ to get 5 Data Scientist Project ideas and a plan 👩🏻💻 ♻️ repost to share with friends. Here is how to become a data scientist in 2026 and beyond 📈 the original video was 4 min Andi had to cut it down to 3 because instagram. Should I do a part 3v what are other skills that you would add to the list and let me know what I should cover in the next video 👩🏻💻 #datascientist #datascience #python #machinelearning #sql #ai
Top Creators
Most active in #data-analytics-and-machine-learning
Reels Graph Intelligence.
Advanced mapping of high-affinity Instagram Reels semantic patterns identified within the #data-analytics-and-machine-learning ecosystem.
Strategic Implementation
Our semantic engine has identified these specific pattern clusters as high-affinity matches for #data-analytics-and-machine-learning. Integrated usage of #data-analytics-and-machine-learning with strategic Reels tags like #learning and #machine learning is statistically linked to a significant increase in initial Reels discovery velocity.
In-Depth Hashtag Analysis: #data-analytics-and-machine-learning
Expert Review • June 4, 2026 • Based on 12 Reels
Executive Overview
#data-analytics-and-machine-learning is an actively used Instagram hashtag. Across the 12 trending reels analyzed on this page, the content has accumulated a combined total of 5,914,884 views— demonstrating strong content velocity within this content vertical. The top creator ecosystem features 8 notable accounts, led by @marytheanalyst with 1,807,125 total views. The hashtag's semantic network includes 17 related keywords such as #learning, #machine learning, #learn, indicating its position within a broader content cluster.
Viewership & Reach Analysis
The 12 reels in this dataset have generated a combined 5,914,884 views, translating to an average of 492,907 views per reel. This strong average viewership suggests healthy algorithmic distribution. Reels using this hashtag are reliably reaching audiences interested in this niche.
The highest-performing reel in this dataset received 1,807,125 views. This viral outlier performance is 367% of the average reel performance in this set. This significant gap between the top performer and the average highlights the "viral lottery" nature of this hashtag — breakout hits can achieve massive scale.
Content Overview & Top Creators
The #data-analytics-and-machine-learning ecosystem is dominated by short-form video content (Reels), aligning with Instagram's algorithmic preference for video-first distribution. There are 8 distinct accounts contributing to the trending feed. The top creator, @marytheanalyst, has contributed 1 reel with a total viewership of 1,807,125. The top three creators — @marytheanalyst, @sundaskhalidd, and @chrisoh.zip — together account for 71.3% of the total views in this dataset. The semantic network of #data-analytics-and-machine-learning extends across 17 related hashtags, including #learning, #machine learning, #learn, #learnings. Creators often use these tags together to reach overlapping audiences.
Discoverability & Reach Potential
The discoverability metrics for #data-analytics-and-machine-learning indicate an active content ecosystem. The average of 492,907 views per reel demonstrates consistent audience reach. For creators using #data-analytics-and-machine-learning, posting consistently with trending audio and relevant angles will help you get noticed.
Analyst Verdict
#data-analytics-and-machine-learning demonstrates the hallmarks of a well-performing Instagram hashtag. With an average of 492,907 views per reel, the viewership metrics position this hashtag as a reliable reach driver. Creators like @marytheanalyst and @sundaskhalidd are leading the charge, setting viewership benchmarks for the community.
Frequently Asked Questions
Everything about #data-analytics-and-machine-learning on Instagram
Global Reels Trends
Explore high-velocity Instagram Reels hashtags currently shaping global discovery.










