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BigDataAnalytics-Lecture.pdf
10.2 MB
Notes on HDFS, MapReduce, YARN, Hadoop vs. traditional systems and much more... from Columbia University.
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📚 Data Science Riddle

You fit a forecasting model and residuals show increasing variance. What is needed?
Anonymous Quiz
20%
Differnecing
48%
Smoothing
26%
Decomposition
7%
Box-Cox
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4 Pillars of Data Science
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AI vs Machine Learning vs Deep Learning Vs Generative AI
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📚 Data Science Riddle

A numeric feature has many repeated exact values with occasional jumps. What type of variable is this?
Anonymous Quiz
30%
Discrete
22%
Ordinal
16%
Continuous
31%
Interval
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Machine Learning Notes.pdf
226.8 KB
A Stanford CS' Lecture note diving into supervised/unsupervised algorithms, neural networks, SVMs with math proofs and Python pseudocode.
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Kafka 101
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📚 Data Science Riddle

Two team members run the same notebook but get different results. What's the culprit?
Anonymous Quiz
7%
Loss Curves
12%
Batch shapes
58%
Random seeds
23%
Metric choice
The Simplest Machine Learning Cheatsheet
5👍1
📚 Data Science Riddle

A query runs slowly due to large table scans. What's the most targeted fix?
Anonymous Quiz
55%
Add indexes
17%
Use aliases
16%
Add DISTINCT
13%
Increase RAM
Everything You need To Know About Databricks
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📚 Data Science Riddle

You want to detect extreme values visually in one plot. Which one is best?
Anonymous Quiz
52%
Box plot
30%
Heatmap
10%
Line chart
8%
Area plot
Mining of Massive Datasets (Leskovec, Stanford).pdf
2.9 MB
The Big Data bible from Stanford: MapReduce, Spark, recommendation systems, PageRank, locality-sensitive hashing, Large scale machine learning and mining social networks/streams all explained clearly with real algorithms you can code today. 500 pages of pure gold.
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If you want to become a Data Scientist, this is the path to follow.
👍5
📚 Data Science Riddle

You want to prevent inconsistent data across environments. What helps most?
Anonymous Quiz
31%
Checkpoints
19%
Contracts
40%
Indexes
10%
Sharding
🛠️ Running Code in Jupyter Notebooks

Jupyter Notebooks let you write & run code interactively.
Here’s a quick guide to make your workflow smoother:

▶️ Kernel & Code Cells
- Each notebook is tied to a single kernel (e.g. IPython).
- Code cells are where you write and execute code.

⌨️ Useful Shortcuts
- Shift + Enter → run current cell, move to next
- Alt + Enter → run current cell, insert new one below
- Ctrl + Enter → run current cell, stay in place

🔄 Kernel Management
- Interrupt the kernel if code hangs.
- Restart kernel to reset memory & variables.

🖥️ Output Handling
- Results & errors appear directly under the cell.
- Long-running code outputs appear as they’re generated.
- Large outputs can be scrolled or collapsed for clarity.

💡 Pro Tip:
Always “Restart & Run All” before sharing or saving a notebook.
This ensures reproducibility and clean results.

👉   Explore
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📚 Data Science Riddle

You need fast reads of small files. What storage options fits best?
Anonymous Quiz
26%
Distributed FS
9%
Cold storage
18%
Object Storage
47%
Local SSD
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6 Must-Know Data Engineering Tools For Beginners
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📚 Data Science Riddle

A feature has low importance but domain experts insist it matters. What do you do?
Anonymous Quiz
30%
Encode it differently
17%
Scale it
13%
Drop the feature
40%
Check interaction effects
Advanced Data Science on Spark.pdf
1.8 MB
Covers Spark for ML, graph processing (GraphFrames), and integration with Hadoop from Stanford University.
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2025/12/07 03:21:16
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