Do you know the average configuration laptop can make your performance average? .No kidding it’s true! especially Data Science Environment involves complex computations. Mostly Deep learning platform like tensor flow etc needs GPU to perform well. Therefore, Replacing your old laptop could be a great deal. I am also a data scientist and When I stuck in searching for the best laptop for me. I decided to share the solution with everybody. So this article will cover Top 5 Laptop for Data Scientist and Developers for this time.
Here you will get a big variety and range of data science laptops. All have different prices and features. You can always make the list for good to have features and must-have features in laptop selection. So while preparing this list we have to shortlist only that laptop which contains at least must-have features. On top of it, If it has a higher cost ( like Mac Book Pro ), It has features that can make your life awesome ( good to have ).
I personally love Mac Book Pro. Even I am a Mac Book Pro user. I never recommend going through my personal preference. In fact when you see its configuration. You will come to know why it is one of the best Laptop for Data Scientist. Here are some details for Mac Book Pro configuration is –
- Screen Size for Mac Book Pro: 16 inches.
- RAM for Mac Book Pro: 16GB DDR3 RAM.
- Graphics card for Mac Book Pro: AMD Radeon Pro 5300M Graphics with GDDR6 memory, Intel UHD Graphics 630
- Operating System for Mac Book Pro: macOS Sierra.
- Storage for Mac Book Pro: 512GB SSD.
- Processor for Mac Book Pro: 6-Core Intel Core i7 Processor
- Weight for Mac Book Pro: 6.4 lbs
The unique selling point for Mac Book Pro –
- Six-speaker system with force-canceling woofers.
- Resolution of 2880×1800 with 16 Inch LED.
- Large touchpad.
- Battery life 8-11 hours.
The downside for Mac Book Pro –
RAM not up-gradable.
- Processor – 2.20GHz Intel i7-9750H 10th Gen processor
- RAM-8GB DDR4 RAM
- hard drive- TB Serial ATA
- Screen Size 15.6-inch screen,
- Graphics card –Nvidia GeForce GTX 1650TI 4 GB Graphics
- OS –Windows 10 operating system
- Weight – 1.8kg laptop
It’s not that costly as Mac Book Pro but it has all those must have a feature which a data scientist need while his work. Here are the configuration details for Asus ROG Strix GL702VM-DB71 –
- Screen Size for 17.3 Inches.
- RAM: 16GB DDR3 RAM.
- Graphics card: GeForce GTX 1660TI dedicated graphics card with 6GB RAM.
- Operating System: Windows 10.
- Storage: 512 NVMe GB SSD
- Processor: Intel i7-10750H Processor.
- Weight: 6 lbs
The unique selling point for Asus ROG Strix G712LU-H7015T
- G-Sync Technology. This technology enables your laptops to eliminate screen noise. I mean it gives the feature to auto eliminate visual imperfections and screen tearing.
- 1920×1080 pixels display .
- Intel i7-10750H Processor 2.6 GHz.
- The RED backlit keyboard gives an awesome experience.
- The left side of this laptop – 1 Mini display port, HDMI, 1 USB 3.0, and 1 USB Type-C.
- The right side of this laptop – Kensington lock, 2 USB 3.0, and a 3.5 headphone jack.
- RAM is up-gradable.
The downside for Asus ROG Strix GL702VM-DB71 (Laptop for Data Scientist)
Frankly speaking, It has Average speakers. The battery life is also average.
- Screen Size: 12.3 Inches.
- Storage: 512 GB SSD
- RAM: 16GB RAM.
- Processor: 10th generation Intel Core i7 Processor
- Graphics card: Intel iris.
- Operating System: Windows 10 Pro.
- Weight: 1.73 lbs (0.78 kg)
The unique selling point for Microsoft Surface Pro-
1. Microsoft Surface Pro is very light weighted. It has 0.77 Kg in weight only.
2. Microsoft Surface Pro has a stylus pen. This pen is considered as the fasted pen of this time. This can ease every data scientist while designing. ( Maybe not available on newer version )
3. Microsoft Surface Pro has 1 USB 4.0,1 micro-SD card slot and displays port.
4. Actually this series has many laptop model variants. So while purchasing you can choose the configuration as per your need.
5. It has an awesome battery backup.
The downside for Microsoft Surface Pro –
The price is very high.
- Screen Size: 15.6 Inches.
- Storage: 1 TB SSD
- RAM: 16GB DDR4 RAM.
- Processor: Intel Core i7-10TH Generation
- Graphics card: RTX 2070 8GB GDDR6.
- Operating System: Windows 10.
- Weight: 2.25 kg
The unique selling point forLenovo Legion 7
- It has a very large display of 15.3 Inches. Hence Some time while data visualization. Big screen laptops are preferred.
- Speakers give awesome sound.
The downside for Lenovo Lenovo Legion 7 –
It’s quite heavy. Although It happens when you have a larger screen.
- Screen Size: 14 Inches.
- Storage: 512GB SSD
- RAM: 8 GB DDR4 RAM.
- Processor: Intel 11th Gen i5-1135G7
- Graphics card: Nvidia MX 350 2GB Graphics
- Operating System: Windows 10.
- Weight: 1.4 kg
The unique selling point for Dell Inspiron 5409
- Perfect battery backup of 4-5 hours in data science stuffs.
- It has a 1-inch thickness with a solid body.
The downside for Dell Inspiron 5409–
This laptop has a TN display. All of the above mention laptops are having the best viewing angle display. Here this laptop is a little behind. Although It has a good display and sufficient for data science work.
Why data Scientist needs more?
If you are a game developer or animator or big data analyst or data scientist, You need more. The reason is very clear. Generally, Every machine learning ( or above mention use type ) code involves many inline machine instruction than usual programming. Although the code size for a machine learning problem is small. The reason is we use some framework while writing code. Therefore, we need to just call a function as define in the library and framework. Actually when you see the Inline machine-level code. It has high complexity hence more computation.
See. When you need to perform multi instruction per machine cycle, you need a multi-core processor and supportive RAM. Even if you have high-performance multi-core CPU and supports up to date RAM but with HDD. Your overall performance will be slower because HDDs have slower Input output operations. Nowadays SSDs are the latest and fast for storage. When you put altogether then you will get great performance.
How much an average laptop can slow down your performance( My personal Exp ) –
It’s my personal experience of running a TensorFlow code on My Lenovo G50 with I5 and 8 GB RAM with RADEON GRAPHICS. It usually takes 10 minutes to train the model. While when I switch into MacBook Pro it starts finishing the same training of model in 5 minutes and 34 seconds. So I saved 4 minutes and 43 seconds at each iteration.
As a data scientist, I need to perform such operations at least 12 times a day. So on round off, it helps me in saving my 45 minutes every day. It’s not a completely accurate calculation but almost accurate.
End Notes –
See this list of best laptop for the data scientist is dynamic. If any new release comes into the picture, we update the content. So at the time of reading this article if you think there should be some change in the list, please let us know. In case if you have any other suggestions please write into the comment box.
The list for Top 5 Laptop for Data Scientist. This list is completely based on my personal opinion and experience about the topic.
Data Science Learner Team.
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